--- imach/src/imach.c 2021/02/20 15:44:02 1.306 +++ imach/src/imach.c 2022/07/22 12:30:08 1.323 @@ -1,6 +1,73 @@ -/* $Id: imach.c,v 1.306 2021/02/20 15:44:02 brouard Exp $ +/* $Id: imach.c,v 1.323 2022/07/22 12:30:08 brouard Exp $ $State: Exp $ $Log: imach.c,v $ + Revision 1.323 2022/07/22 12:30:08 brouard + * imach.c (Module): Output of Wald test in the htm file and not only in the log. + + Revision 1.322 2022/07/22 12:27:48 brouard + * imach.c (Module): Output of Wald test in the htm file and not only in the log. + + Revision 1.321 2022/07/22 12:04:24 brouard + Summary: r28 + + * imach.c (Module): Output of Wald test in the htm file and not only in the log. + + Revision 1.320 2022/06/02 05:10:11 brouard + *** empty log message *** + + Revision 1.319 2022/06/02 04:45:11 brouard + * imach.c (Module): Adding the Wald tests from the log to the main + htm for better display of the maximum likelihood estimators. + + Revision 1.318 2022/05/24 08:10:59 brouard + * imach.c (Module): Some attempts to find a bug of wrong estimates + of confidencce intervals with product in the equation modelC + + Revision 1.317 2022/05/15 15:06:23 brouard + * imach.c (Module): Some minor improvements + + Revision 1.316 2022/05/11 15:11:31 brouard + Summary: r27 + + Revision 1.315 2022/05/11 15:06:32 brouard + *** empty log message *** + + Revision 1.314 2022/04/13 17:43:09 brouard + * imach.c (Module): Adding link to text data files + + Revision 1.313 2022/04/11 15:57:42 brouard + * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed + + Revision 1.312 2022/04/05 21:24:39 brouard + *** empty log message *** + + Revision 1.311 2022/04/05 21:03:51 brouard + Summary: Fixed quantitative covariates + + Fixed covariates (dummy or quantitative) + with missing values have never been allowed but are ERRORS and + program quits. Standard deviations of fixed covariates were + wrongly computed. Mean and standard deviations of time varying + covariates are still not computed. + + Revision 1.310 2022/03/17 08:45:53 brouard + Summary: 99r25 + + Improving detection of errors: result lines should be compatible with + the model. + + Revision 1.309 2021/05/20 12:39:14 brouard + Summary: Version 0.99r24 + + Revision 1.308 2021/03/31 13:11:57 brouard + Summary: Version 0.99r23 + + + * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett + + Revision 1.307 2021/03/08 18:11:32 brouard + Summary: 0.99r22 fixed bug on result: + Revision 1.306 2021/02/20 15:44:02 brouard Summary: Version 0.99r21 @@ -1051,6 +1118,7 @@ Important routines #define POWELLNOF3INFF1TEST /* Skip test */ /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */ /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */ +/* #define FLATSUP *//* Suppresses directions where likelihood is flat */ #include #include @@ -1117,7 +1185,7 @@ typedef struct { #define NINTERVMAX 8 #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */ #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */ -#define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */ +#define NCOVMAX 30 /**< Maximum number of covariates, including generated covariates V1*V2 */ #define codtabm(h,k) (1 & (h-1) >> (k-1))+1 /*#define decodtabm(h,k,cptcoveff)= (h <= (1<> (k-1)) & 1) +1 : -1)*/ #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1 @@ -1141,12 +1209,12 @@ typedef struct { #define ODIRSEPARATOR '\\' #endif -/* $Id: imach.c,v 1.306 2021/02/20 15:44:02 brouard Exp $ */ +/* $Id: imach.c,v 1.323 2022/07/22 12:30:08 brouard Exp $ */ /* $State: Exp $ */ #include "version.h" char version[]=__IMACH_VERSION__; -char copyright[]="Feb 2021,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, INED 2000-2021"; -char fullversion[]="$Revision: 1.306 $ $Date: 2021/02/20 15:44:02 $"; +char copyright[]="July 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022"; +char fullversion[]="$Revision: 1.323 $ $Date: 2022/07/22 12:30:08 $"; char strstart[80]; char optionfilext[10], optionfilefiname[FILENAMELENGTH]; int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */ @@ -1327,19 +1395,48 @@ double ***cotvar; /* Time varying covari double ***cotqvar; /* Time varying quantitative covariate itqv */ double idx; int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */ -/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ -/*k 1 2 3 4 5 6 7 8 9 */ -/*Tvar[k]= 5 4 3 6 5 2 7 1 1 */ -/* Tndvar[k] 1 2 3 4 5 */ -/*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */ -/* Tns[k] 1 2 2 4 5 */ /* Number of single cova */ -/* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */ -/* TvarsDind 2 3 9 */ /* position K of single dummy cova */ -/* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */ -/* TvarsQind 1 6 */ /* position K of single quantitative cova */ -/* Tprod[i]=k 4 7 */ -/* Tage[i]=k 5 8 */ -/* */ +/* Some documentation */ + /* Design original data + * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12 + * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv + * ntv=3 nqtv=1 + * cptcovn number of covariates (not including constant and age) = # of + plus 1 = 10+1=11 + * For time varying covariate, quanti or dummies + * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti + * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti + * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1 + * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1 + * covar[k,i], value of kth fixed covariate dummy or quanti : + * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8) + * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10 + * k= 1 2 3 4 5 6 7 8 9 10 11 + */ +/* According to the model, more columns can be added to covar by the product of covariates */ +/* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1 + # States 1=Coresidence, 2 Living alone, 3 Institution + # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi +*/ +/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ +/* k 1 2 3 4 5 6 7 8 9 */ +/*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/ + /* fixed or varying), 1 for age product, 2 for*/ + /* product */ +/*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */ + /*(single or product without age), 2 dummy*/ + /* with age product, 3 quant with age product*/ +/*Tvar[k]= 5 4 3 6 5 2 7 1 1 */ +/* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */ +/*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/ +/*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */ +/* nsq 1 2 */ /* Counting single quantit tv */ +/* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */ +/* TvarsQind 1 6 */ /* position K of single quantitative cova */ +/* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */ +/* cptcovage 1 2 */ /* Counting cov*age in the model equation */ +/* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */ +/* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */ +/* TvarF TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */ +/* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */ /* Type */ /* V 1 2 3 4 5 */ /* F F V V V */ @@ -1350,17 +1447,21 @@ int *TvarsDind; int *TvarsQ; int *TvarsQind; -#define MAXRESULTLINES 10 +#define MAXRESULTLINESPONE 10+1 int nresult=0; int parameterline=0; /* # of the parameter (type) line */ -int TKresult[MAXRESULTLINES]; -int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */ -int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */ -int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */ -double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */ -double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */ -int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */ - +int TKresult[MAXRESULTLINESPONE]; +int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */ +int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */ +int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */ +double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */ +double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */ +int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */ + +/* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1 + # States 1=Coresidence, 2 Living alone, 3 Institution + # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi +*/ /* int *TDvar; /\**< TDvar[1]=4, TDvarF[2]=3, TDvar[3]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */ int *TvarF; /**< TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ int *TvarFind; /**< TvarFind[1]=6, TvarFind[2]=7, Tvarind[3]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ @@ -1562,7 +1663,7 @@ char *cutl(char *blocc, char *alocc, cha { /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ' and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2') - gives blocc="abcdef" and alocc="ghi2j". + gives alocc="abcdef" and blocc="ghi2j". If occ is not found blocc is null and alocc is equal to in. Returns blocc */ char *s, *t; @@ -1844,7 +1945,9 @@ char *subdirf(char fileres[]) /*************** function subdirf2 ***********/ char *subdirf2(char fileres[], char *preop) { - + /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte" + Errors in subdirf, 2, 3 while printing tmpout is + rewritten within the same printf. Workaround: many printfs */ /* Caution optionfilefiname is hidden */ strcpy(tmpout,optionfilefiname); strcat(tmpout,"/"); @@ -2215,10 +2318,10 @@ void linmin(double p[], double xi[], int #endif #ifdef LINMINORIGINAL #else - if(fb == fx){ /* Flat function in the direction */ - xmin=xx; + if(fb == fx){ /* Flat function in the direction */ + xmin=xx; *flat=1; - }else{ + }else{ *flat=0; #endif /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */ @@ -2276,10 +2379,10 @@ void linmin(double p[], double xi[], int /*************** powell ************************/ /* -Minimization of a function func of n variables. Input consists of an initial starting point -p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di- -rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value -such that failure to decrease by more than this amount on one iteration signals doneness. On +Minimization of a function func of n variables. Input consists in an initial starting point +p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di- +rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value +such that failure to decrease by more than this amount in one iteration signals doneness. On output, p is set to the best point found, xi is the then-current direction set, fret is the returned function value at p , and iter is the number of iterations taken. The routine linmin is used. */ @@ -2304,12 +2407,6 @@ void powell(double p[], double **xi, int double fp,fptt; double *xits; int niterf, itmp; -#ifdef LINMINORIGINAL -#else - - flatdir=ivector(1,n); - for (j=1;j<=n;j++) flatdir[j]=0; -#endif pt=vector(1,n); ptt=vector(1,n); @@ -2433,14 +2530,14 @@ void powell(double p[], double **xi, int /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */ /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */ /* New value of last point Pn is not computed, P(n-1) */ - for(j=1;j<=n;j++) { - if(flatdir[j] >0){ - printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]); - fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]); - } - /* printf("\n"); */ - /* fprintf(ficlog,"\n"); */ + for(j=1;j<=n;j++) { + if(flatdir[j] >0){ + printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]); + fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]); } + /* printf("\n"); */ + /* fprintf(ficlog,"\n"); */ + } /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */ if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */ /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */ @@ -2478,10 +2575,6 @@ void powell(double p[], double **xi, int } #endif -#ifdef LINMINORIGINAL -#else - free_ivector(flatdir,1,n); -#endif free_vector(xit,1,n); free_vector(xits,1,n); free_vector(ptt,1,n); @@ -2595,6 +2688,13 @@ void powell(double p[], double **xi, int } printf("\n"); fprintf(ficlog,"\n"); +#ifdef FLATSUP + free_vector(xit,1,n); + free_vector(xits,1,n); + free_vector(ptt,1,n); + free_vector(pt,1,n); + return; +#endif } #endif printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig); @@ -2679,23 +2779,28 @@ void powell(double p[], double **xi, int newm=savm; /* Covariates have to be included here again */ cov[2]=agefin; - if(nagesqr==1) - cov[3]= agefin*agefin;; + if(nagesqr==1){ + cov[3]= agefin*agefin; + } for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)]; + /* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; */ /* printf("prevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */ } for (k=1; k<=nsq;k++) { /* For single varying covariates only */ /* Here comes the value of quantitative after renumbering k with single quantitative covariates */ - cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; + cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; + /* cov[++k1]=Tqresult[nres][k]; */ /* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); */ } for (k=1; k<=cptcovage;k++){ /* For product with age */ - if(Dummy[Tvar[Tage[k]]]){ + if(Dummy[Tage[k]]==2){ /* dummy with age */ cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; - } else{ - cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; + /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */ + } else if(Dummy[Tage[k]]==3){ /* quantitative with age */ + cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; + /* cov[++k1]=Tqresult[nres][k]; */ } /* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */ } @@ -2704,14 +2809,18 @@ void powell(double p[], double **xi, int if(Dummy[Tvard[k][1]==0]){ if(Dummy[Tvard[k][2]==0]){ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; + /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */ }else{ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; + /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */ } }else{ if(Dummy[Tvard[k][2]==0]){ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; + /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */ }else{ cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; + /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */ } } } @@ -2720,7 +2829,7 @@ void powell(double p[], double **xi, int /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/ /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */ - /* age and covariate values of ij are in 'cov' */ + /* age and covariate values of ij are in 'cov' */ out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */ savm=oldm; @@ -2760,8 +2869,16 @@ void powell(double p[], double **xi, int if(!first){ first=1; printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d). Others in log file only...\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax); + fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax); + }else if (first >=1 && first <10){ + fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax); + first++; + }else if (first ==10){ + fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax); + printf("Warning: the stable prevalence dit not converge. This warning came too often, IMaCh will stop notifying, even in its log file. Look at the graphs to appreciate the non convergence.\n"); + fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n"); + first++; } - fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax); /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */ free_vector(min,1,nlstate); @@ -2835,8 +2952,9 @@ void powell(double p[], double **xi, int /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */ /* Covariates have to be included here again */ cov[2]=agefin; - if(nagesqr==1) + if(nagesqr==1){ cov[3]= agefin*agefin;; + } for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)]; @@ -2857,10 +2975,11 @@ void powell(double p[], double **xi, int /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */ /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */ for (k=1; k<=cptcovage;k++){ /* For product with age */ - if(Dummy[Tvar[Tage[k]]]){ + /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ ERROR ???*/ + if(Dummy[Tage[k]]== 2){ /* dummy with age */ cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; - } else{ - cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; + } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */ + cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; } /* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */ } @@ -2930,7 +3049,7 @@ void powell(double p[], double **xi, int maxmax=0.; for(i=1; i<=nlstate; i++){ - meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */ + meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */ maxmax=FMAX(maxmax,meandiff[i]); /* printf("Back age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, i, meandiff[i],(int)agefin, i, max[i], i, min[i],maxmax); */ } /* i loop */ @@ -3064,7 +3183,9 @@ double **pmij(double **ps, double *cov, doldm=ddoldms; /* global pointers */ dnewm=ddnewms; dsavm=ddsavms; - + + /* Debug */ + /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */ agefin=cov[2]; /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */ /* bmij *//* age is cov[2], ij is included in cov, but we need for @@ -3284,29 +3405,53 @@ double ***hpxij(double ***po, int nhstep cov[1]=1.; agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */ cov[2]=agexact; - if(nagesqr==1) + if(nagesqr==1){ cov[3]= agexact*agexact; + } for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ - /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ +/* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ + /* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 */ +/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ +/* k 1 2 3 4 5 6 7 8 9 */ +/*Tvar[k]= 5 4 3 6 5 2 7 1 1 */ +/* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */ +/*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/ +/*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */ cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)]; /* printf("hpxij Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */ } for (k=1; k<=nsq;k++) { /* For single varying covariates only */ /* Here comes the value of quantitative after renumbering k with single quantitative covariates */ - cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; + cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; /* printf("hPxij Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); */ } - for (k=1; k<=cptcovage;k++){ - if(Dummy[Tvar[Tage[k]]]){ + for (k=1; k<=cptcovage;k++){ /* For product with age V1+V1*age +V4 +age*V3 */ + /* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*/ + /* */ + if(Dummy[Tage[k]]== 2){ /* dummy with age */ + /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ */ cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; - } else{ - cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; + } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */ + cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; } /* printf("hPxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */ } - for (k=1; k<=cptcovprod;k++){ /* */ + for (k=1; k<=cptcovprod;k++){ /* For product without age */ /* printf("hPxij Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); */ - cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; + /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */ + if(Dummy[Tvard[k][1]==0]){ + if(Dummy[Tvard[k][2]==0]){ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; + }else{ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; + } + }else{ + if(Dummy[Tvard[k][2]==0]){ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; + }else{ + cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; + } + } } /* for (k=1; k<=cptcovn;k++) */ /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */ @@ -3318,7 +3463,7 @@ double ***hpxij(double ***po, int nhstep /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/ /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/ - /* right multiplication of oldm by the current matrix */ + /* right multiplication of oldm by the current matrix */ out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmij(pmmij,cov,ncovmodel,x,nlstate)); /* if((int)age == 70){ */ @@ -3388,6 +3533,8 @@ double ***hbxij(double ***po, int nhstep cov[1]=1.; agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */ /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */ + /* Debug */ + /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */ cov[2]=agexact; if(nagesqr==1) cov[3]= agexact*agexact; @@ -3402,10 +3549,11 @@ double ***hbxij(double ***po, int nhstep cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; /* printf("hPxij Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); */ } - for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */ - if(Dummy[Tvar[Tage[k]]]){ + for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 *//* For product with age */ + /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age error!!!*\/ */ + if(Dummy[Tage[k]]== 2){ /* dummy with age */ cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; - } else{ + } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */ cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; } /* printf("hBxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */ @@ -3507,11 +3655,16 @@ double func( double *x) */ ioffset=2+nagesqr ; /* Fixed */ - for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */ - cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/ + for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */ + /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */ + /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + /* TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */ + /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */ + cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/ + /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */ } /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4] - is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2] + is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6 has been calculated etc */ /* For an individual i, wav[i] gives the number of effective waves */ /* We compute the contribution to Likelihood of each effective transition @@ -3523,8 +3676,8 @@ double func( double *x) meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i] */ for(mi=1; mi<= wav[i]-1; mi++){ - for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/ - /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */ + for(k=1; k <= ncovv ; k++){ /* Varying covariates in the model (single and product but no age )"V5+V4+V3+V4*V3+V5*age+V1*age+V1" +TvarVind 1,2,3,4(V4*V3) Tvar[1]@7{5, 4, 3, 6, 5, 1, 1 ; 6 because the created covar is after V5 and is 6, minus 1+1, 3,2,1,4 positions in cotvar*/ + /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */ cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; } for (ii=1;ii<=nlstate+ndeath;ii++) @@ -3539,10 +3692,10 @@ double func( double *x) if(nagesqr==1) cov[3]= agexact*agexact; /* Should be changed here */ for (kk=1; kk<=cptcovage;kk++) { - if(!FixedV[Tvar[Tage[kk]]]) - cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */ - else - cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; + if(!FixedV[Tvar[Tage[kk]]]) + cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */ + else + cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; } out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); @@ -3650,8 +3803,13 @@ double func( double *x) } /* end of individual */ } else if(mle==2){ for (i=1,ipmx=0, sw=0.; i<=imx; i++){ - for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; + ioffset=2+nagesqr ; + for (k=1; k<=ncovf;k++) + cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i]; for(mi=1; mi<= wav[i]-1; mi++){ + for(k=1; k <= ncovv ; k++){ + cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; + } for (ii=1;ii<=nlstate+ndeath;ii++) for (j=1;j<=nlstate+ndeath;j++){ oldm[ii][j]=(ii==j ? 1.0 : 0.0); @@ -3829,7 +3987,7 @@ double funcone( double *x) /* Fixed */ /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */ /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */ - for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */ + for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */ cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/ /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */ /* cov[2+6]=covar[Tvar[6]][i]; */ @@ -4008,7 +4166,7 @@ void likelione(FILE *ficres,double p[], void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double [])) { - int i,j, iter=0; + int i,j,k, jk, jkk=0, iter=0; double **xi; double fret; double fretone; /* Only one call to likelihood */ @@ -4042,8 +4200,65 @@ void mlikeli(FILE *ficres,double p[], in if(j!=i)fprintf(ficrespow," p%1d%1d",i,j); fprintf(ficrespow,"\n"); #ifdef POWELL +#ifdef LINMINORIGINAL +#else /* LINMINORIGINAL */ + + flatdir=ivector(1,npar); + for (j=1;j<=npar;j++) flatdir[j]=0; +#endif /*LINMINORIGINAL */ + +#ifdef FLATSUP + powell(p,xi,npar,ftol,&iter,&fret,flatdir,func); + /* reorganizing p by suppressing flat directions */ + for(i=1, jk=1; i <=nlstate; i++){ + for(k=1; k <=(nlstate+ndeath); k++){ + if (k != i) { + printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]); + if(flatdir[jk]==1){ + printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]); + } + for(j=1; j <=ncovmodel; j++){ + printf("%12.7f ",p[jk]); + jk++; + } + printf("\n"); + } + } + } +/* skipping */ + /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */ + for(i=1, jk=1, jkk=1;i <=nlstate; i++){ + for(k=1; k <=(nlstate+ndeath); k++){ + if (k != i) { + printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]); + if(flatdir[jk]==1){ + printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk); + for(j=1; j <=ncovmodel; jk++,j++){ + printf(" p[%d]=%12.7f",jk, p[jk]); + /*q[jjk]=p[jk];*/ + } + }else{ + printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk); + for(j=1; j <=ncovmodel; jk++,jkk++,j++){ + printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk); + /*q[jjk]=p[jk];*/ + } + } + printf("\n"); + } + fflush(stdout); + } + } + powell(p,xi,npar,ftol,&iter,&fret,flatdir,func); +#else /* FLATSUP */ powell(p,xi,npar,ftol,&iter,&fret,func); -#endif +#endif /* FLATSUP */ + +#ifdef LINMINORIGINAL +#else + free_ivector(flatdir,1,npar); +#endif /* LINMINORIGINAL*/ +#endif /* POWELL */ #ifdef NLOPT #ifdef NEWUOA @@ -4071,6 +4286,14 @@ void mlikeli(FILE *ficres,double p[], in } nlopt_destroy(opt); #endif +#ifdef FLATSUP + /* npared = npar -flatd/ncovmodel; */ + /* xired= matrix(1,npared,1,npared); */ + /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */ + /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */ + /* free_matrix(xire,1,npared,1,npared); */ +#else /* FLATSUP */ +#endif /* FLATSUP */ free_matrix(xi,1,npar,1,npar); fclose(ficrespow); printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p)); @@ -4522,7 +4745,7 @@ void freqsummary(char fileres[], double Title=%s
Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
\n",\ fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); } - fprintf(ficresphtm,"Current page is file %s
\n\n

Frequencies and prevalence by age at begin of transition and dummy covariate value at beginning of transition

\n",fileresphtm, fileresphtm); + fprintf(ficresphtm,"Current page is file %s
\n\n

Frequencies (weight=%d) and prevalence by age at begin of transition and dummy covariate value at beginning of transition

\n",fileresphtm, fileresphtm, weightopt); strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm")); if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) { @@ -4532,11 +4755,11 @@ Title=%s
Datafile=%s Firstpass=%d La exit(70); } else{ fprintf(ficresphtmfr,"\nIMaCh PHTM_Frequency table %s\n %s
%s \ -
\n \ +,
\n \ Title=%s
Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
\n",\ fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); } - fprintf(ficresphtmfr,"Current page is file %s
\n\n

Frequencies of all effective transitions of the model, by age at begin of transition, and covariate value at the begin of transition (if the covariate is a varying covariate)

Unknown status is -1
\n",fileresphtmfr, fileresphtmfr); + fprintf(ficresphtmfr,"Current page is file %s
\n\n

(weight=%d) frequencies of all effective transitions of the model, by age at begin of transition, and covariate value at the begin of transition (if the covariate is a varying covariate)

Unknown status is -1
\n",fileresphtmfr, fileresphtmfr,weightopt); y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE); x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE); @@ -4684,10 +4907,13 @@ Title=%s
Datafile=%s Firstpass=%d La if(s[m][iind]==-1) printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d agebegin=%.2f ageend=%.2f, agemed=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind],agebegin, ageend, (int)((agebegin+ageend)/2.)); freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */ - for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */ - idq[z1]=idq[z1]+weight[iind]; - meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */ - stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */ + for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */ + if(!isnan(covar[ncovcol+z1][iind])){ + idq[z1]=idq[z1]+weight[iind]; + meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */ + /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/ + stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */ + } } /* if((int)agev[m][iind] == 55) */ /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */ @@ -4711,7 +4937,7 @@ Title=%s
Datafile=%s Firstpass=%d La /* } */ } /* end bool */ } /* end iind = 1 to imx */ - /* prop[s][age] is feeded for any initial and valid live state as well as + /* prop[s][age] is fed for any initial and valid live state as well as freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */ @@ -4750,16 +4976,19 @@ Title=%s
Datafile=%s Firstpass=%d La Printing means of quantitative variables if any */ for (z1=1; z1<= nqfveff; z1++) { - fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]); + fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]); fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]); if(weightopt==1){ printf(" Weighted mean and standard deviation of"); fprintf(ficlog," Weighted mean and standard deviation of"); fprintf(ficresphtmfr," Weighted mean and standard deviation of"); } - printf(" fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1])); - fprintf(ficlog," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1])); - fprintf(ficresphtmfr," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)

\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1])); + /* mu = \frac{w x}{\sum w} + var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2 + */ + printf(" fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1])); + fprintf(ficlog," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1])); + fprintf(ficresphtmfr," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)

\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1])); } /* for (z1=1; z1<= nqtveff; z1++) { */ /* for(m=1;m<=lastpass;m++){ */ @@ -5262,33 +5491,41 @@ void concatwav(int wav[], int **dh, int for(i=1; i<=imx; i++){ /* For simple cases and if state is death */ mi=0; /* First valid wave */ mli=0; /* Last valid wave */ - m=firstpass; - while(s[m][i] <= nlstate){ /* a live state */ + m=firstpass; /* Loop on waves */ + while(s[m][i] <= nlstate){ /* a live state or unknown state */ if(m >firstpass && s[m][i]==s[m-1][i] && mint[m][i]==mint[m-1][i] && anint[m][i]==anint[m-1][i]){/* Two succesive identical information on wave m */ mli=m-1;/* mw[++mi][i]=m-1; */ }else if(s[m][i]>=1 || s[m][i]==-4 || s[m][i]==-5){ /* Since 0.98r4 if status=-2 vital status is really unknown, wave should be skipped */ - mw[++mi][i]=m; + mw[++mi][i]=m; /* Valid wave: incrementing mi and updating mi; mw[mi] is the wave number of mi_th valid transition */ mli=m; } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */ if(m < lastpass){ /* m < lastpass, standard case */ m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */ } - else{ /* m >= lastpass, eventual special issue with warning */ + else{ /* m = lastpass, eventual special issue with warning */ #ifdef UNKNOWNSTATUSNOTCONTRIBUTING break; #else - if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){ + if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){ /* no death date and known date of interview, case -2 (vital status unknown is warned later */ if(firsthree == 0){ printf("Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath); firsthree=1; + }else if(firsthree >=1 && firsthree < 10){ + fprintf(ficlog,"Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath); + firsthree++; + }else if(firsthree == 10){ + printf("Information, too many Information flags: no more reported to log either\n"); + fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n"); + firsthree++; + }else{ + firsthree++; } - fprintf(ficlog,"Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath); - mw[++mi][i]=m; + mw[++mi][i]=m; /* Valid transition with unknown status */ mli=m; } if(s[m][i]==-2){ /* Vital status is really unknown */ nbwarn++; - if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */ + if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */ printf("Warning! Vital status for individual %ld (line=%d) at last wave %d interviewed at date %d/%d is unknown %d. Please, check if the vital status and the date of death %d/%d are really unknown. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], (int) moisdc[i], (int) andc[i], i, m); fprintf(ficlog,"Warning! Vital status for individual %ld (line=%d) at last wave %d interviewed at date %d/%d is unknown %d. Please, check if the vital status and the date of death %d/%d are really unknown. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], (int) moisdc[i], (int) andc[i], i, m); } @@ -5313,34 +5550,35 @@ void concatwav(int wav[], int **dh, int #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE else if ((int) andc[i] != 9999) { /* Date of death is known */ if ((int)anint[m][i]!= 9999) { /* date of last interview is known */ - if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* death occured before last wave and status should have been death instead of -1 */ + if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* month of death occured before last wave month and status should have been death instead of -1 */ nbwarn++; if(firstfiv==0){ - printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d interviewed at %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m ); + printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m ); firstfiv=1; }else{ - fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d interviewed at %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m ); + fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m ); } - }else{ /* Death occured afer last wave potential bias */ + s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */ + }else{ /* Month of Death occured afer last wave month, potential bias */ nberr++; if(firstwo==0){ - printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictive wave at the date of last vital status scan, with a dead status or alive but unknown state status (-1). See documentation\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m ); + printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m ); firstwo=1; } - fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictive wave at the date of last vital status scan, with a dead status or alive but unknown state status (-1). See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m ); + fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m ); } }else{ /* if date of interview is unknown */ /* death is known but not confirmed by death status at any wave */ if(firstfour==0){ - printf("Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m ); + printf("Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d with status %d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m ); firstfour=1; } - fprintf(ficlog,"Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m ); + fprintf(ficlog,"Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d with status %d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m ); } } /* end if date of death is known */ #endif - wav[i]=mi; /* mi should be the last effective wave (or mli) */ - /* wav[i]=mw[mi][i]; */ + wav[i]=mi; /* mi should be the last effective wave (or mli), */ + /* wav[i]=mw[mi][i]; */ if(mi==0){ nbwarn++; if(first==0){ @@ -5354,7 +5592,10 @@ void concatwav(int wav[], int **dh, int } /* End individuals */ /* wav and mw are no more changed */ - + printf("Information, you have to check %d informations which haven't been logged!\n",firsthree); + fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree); + + for(i=1; i<=imx; i++){ for(mi=1; mi1 ){ - printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i); - fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i); + printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i); + fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i); + fflush(ficlog); + exit(1); } if ((ij < -1) || (ij > NCOVMAX)){ printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX ); @@ -5564,6 +5809,16 @@ void concatwav(int wav[], int **dh, int break; } /* end switch */ } /* end dummy test */ + if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */ + for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/ + if(isnan(covar[Tvar[k]][i])){ + printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i); + fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i); + fflush(ficlog); + exit(1); + } + } + } } /* end of loop on model-covariate k. nbcode[Tvark][1]=-1, nbcode[Tvark][1]=0 and nbcode[Tvark][2]=1 sets the value of covariate k*/ for (k=-1; k< maxncov; k++) Ndum[k]=0; @@ -5877,7 +6132,9 @@ void concatwav(int wav[], int **dh, int varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf; } } - + /* if((int)age ==50){ */ + /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */ + /* } */ /* Computing expectancies */ hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres); for(i=1; i<=nlstate;i++) @@ -6642,7 +6899,8 @@ To be simple, these graphs help to under fprintf(fichtmcov, "\n

********** Variable "); - for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */ + for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); fprintf(fichtmcov, "**********\n
"); fprintf(ficresprobcor, "\n#********** Variable "); @@ -6671,8 +6929,11 @@ To be simple, these graphs help to under */ /* nbcode[1][1]=0 nbcode[1][2]=1;*/ } - /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */ - for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; + /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */ + /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */ + /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */ + for (k=1; k<=cptcovage;k++) + cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; for (k=1; k<=cptcovprod;k++) cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; @@ -6883,12 +7144,12 @@ void printinghtml(char fileresu[], char double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \ double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){ int jj1, k1, i1, cpt, k4, nres; - + /* In fact some results are already printed in fichtm which is open */ fprintf(fichtm,""); - fprintf(fichtm,"
  • model=1+age+%s\n \ -
", model); +/* fprintf(fichtm,"
  • model=1+age+%s\n \ */ +/*
", model); */ fprintf(fichtm,"

  • Result files (first order: no variance)

    \n"); fprintf(fichtm,"
  • - Observed frequency between two states (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): %s (html file)
    \n", jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm")); @@ -6921,7 +7182,7 @@ void printinghtml(char fileresu[], char m=pow(2,cptcoveff); if (cptcovn < 1) {m=1;ncodemax[1]=1;} - fprintf(fichtm," \n
    • Graphs

      • "); + fprintf(fichtm," \n

      • Graphs (first order)

        • "); jj1=0; @@ -6956,7 +7217,7 @@ void printinghtml(char fileresu[], char fprintf(fichtm,""); } /* cptcovn >0 */ } - fprintf(fichtm," \n

      "); + fprintf(fichtm," \n
    "); jj1=0; @@ -6990,7 +7251,7 @@ void printinghtml(char fileresu[], char } /* if(nqfveff+nqtveff 0) */ /* Test to be done */ - fprintf(fichtm," ************\n
    "); + fprintf(fichtm," (model=%s) ************\n
    ",model); if(invalidvarcomb[k1]){ fprintf(fichtm,"\n

    Combination (%d) ignored because no cases

    \n",k1); printf("\nCombination (%d) ignored because no cases \n",k1); @@ -7035,8 +7296,10 @@ divided by h: hPij if(prevfcast==1){ /* Projection of prevalence up to period (forward stable) prevalence in each health state */ for(cpt=1; cpt<=nlstate;cpt++){ - fprintf(fichtm,"
    \n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), from year %.1f up to year %.1f tending to period (stable) forward prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). %s_%d-%d-%d.svg
    \ -", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres); + fprintf(fichtm,"
    \n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), from year %.1f up to year %.1f tending to period (stable) forward prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). %s_%d-%d-%d.svg", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres); + fprintf(fichtm," (data from text file %s.txt)\n
    ",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_")); + fprintf(fichtm,"", + subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres); } } if(prevbcast==1){ @@ -7045,14 +7308,16 @@ divided by h: hPij fprintf(fichtm,"
    \n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \ from year %.1f up to year %.1f (probably close to stable [mixed] back prevalence in state %d (randomness in cross-sectional prevalence is not taken into \ account but can visually be appreciated). Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) \ -with weights corresponding to observed prevalence at different ages. %s_%d-%d-%d.svg
    \ - ", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres); +with weights corresponding to observed prevalence at different ages. %s_%d-%d-%d.svg", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres); + fprintf(fichtm," (data from text file %s.txt)\n
    ",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_")); + fprintf(fichtm," ", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres); } } for(cpt=1; cpt<=nlstate;cpt++) { - fprintf(fichtm,"\n
    - Life expectancy by health state (%d) at initial age and its decomposition into health expectancies in each alive state (1 to %d) (or area under each survival functions): %s_%d-%d-%d.svg
    \ -",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres); + fprintf(fichtm,"\n
    - Life expectancy by health state (%d) at initial age and its decomposition into health expectancies in each alive state (1 to %d) (or area under each survival functions): %s_%d-%d-%d.svg",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres); + fprintf(fichtm," (data from text file %s.txt)\n
    ",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_")); + fprintf(fichtm,"", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres ); } /* } /\* end i1 *\/ */ }/* End k1 */ @@ -7104,11 +7369,47 @@ See page 'Matrix of variance-covariance /* else */ /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=%s (instead of .)

    • \n",popforecast, stepm, model); */ fflush(fichtm); - fprintf(fichtm,"
    • Graphs

      • "); m=pow(2,cptcoveff); if (cptcovn < 1) {m=1;ncodemax[1]=1;} + fprintf(fichtm,"

      • Graphs (second order)

        • "); + + jj1=0; + + fprintf(fichtm," \n

        "); + jj1=0; for(nres=1; nres <= nresult; nres++){ /* For each resultline */ @@ -7118,15 +7419,26 @@ See page 'Matrix of variance-covariance /* for(i1=1; i1<=ncodemax[k1];i1++){ */ jj1++; if (cptcovn > 0) { + fprintf(fichtm,"\n

        "); + fprintf(fichtm,"

        ************ Results for covariates"); - for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */ + for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */ fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]); + printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout); /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */ + } for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); } - fprintf(fichtm," ************\n
        "); + fprintf(fichtm," (model=%s) ************\n
        ",model); if(invalidvarcomb[k1]){ fprintf(fichtm,"\n

        Combination (%d) ignored because no cases

        \n",k1); @@ -7135,15 +7447,17 @@ See page 'Matrix of variance-covariance } for(cpt=1; cpt<=nlstate;cpt++) { fprintf(fichtm,"\n
        - Observed (cross-sectional with mov_average=%d) and period (incidence based) \ -prevalence (with 95%% confidence interval) in state (%d):         %s_%d-%d-%d.svg\n
        \ -",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres); +prevalence (with 95%% confidence interval) in state (%d): %s_%d-%d-%d.svg",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres); + fprintf(fichtm," (data from text file %s)\n
        ",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_")); + fprintf(fichtm,"",subdirf2(optionfilefiname,"V_"), cpt,k1,nres); } fprintf(fichtm,"\n
        - Total life expectancy by age and \ -health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \ +health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \ true period expectancies (those weighted with period prevalences are also\ drawn in addition to the population based expectancies computed using\ - observed and cahotic prevalences: %s_%d-%d.svg\n
        \ -",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres); + observed and cahotic prevalences: %s_%d-%d.svg",nlstate, subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres); + fprintf(fichtm," (data from text file %s.txt) \n
        ",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_")); + fprintf(fichtm,"",subdirf2(optionfilefiname,"E_"),k1,nres); /* } /\* end i1 *\/ */ }/* End k1 */ }/* End nres */ @@ -7260,7 +7574,7 @@ void printinggnuplot(char fileresu[], ch fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres); fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres); /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */ - fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel); + fprintf(ficgp,"set title \"Alive state %d %s model=%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model); fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres); /* fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); */ /* k1-1 error should be nres-1*/ @@ -9364,23 +9678,23 @@ int readdata(char datafile[], int firsto } if(lval <-1 || lval >1){ printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \ - Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \ + Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \ for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \ For example, for multinomial values like 1, 2 and 3,\n \ build V1=0 V2=0 for the reference value (1),\n \ V1=1 V2=0 for (2) \n \ and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \ output of IMaCh is often meaningless.\n \ - Exiting.\n",lval,linei, i,line,j); + Exiting.\n",lval,linei, i,line,iv,j); fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \ - Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \ + Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \ for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \ For example, for multinomial values like 1, 2 and 3,\n \ build V1=0 V2=0 for the reference value (1),\n \ V1=1 V2=0 for (2) \n \ and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \ output of IMaCh is often meaningless.\n \ - Exiting.\n",lval,linei, i,line,j);fflush(ficlog); + Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog); return 1; } cotvar[j][iv][i]=(double)(lval); @@ -9488,6 +9802,8 @@ int readdata(char datafile[], int firsto cutv(stra, strb, line, ' '); if(strb[0]=='.') { /* Missing value */ lval=-1; + coqvar[iv][i]=NAN; + covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */ }else{ errno=0; /* what_kind_of_number(strb); */ @@ -9591,7 +9907,6 @@ int decoderesult ( char resultline[], in char stra[80], strb[80], strc[80], strd[80],stre[80]; removefirstspace(&resultline); - printf("decoderesult:%s\n",resultline); if (strstr(resultline,"v") !=0){ printf("Error. 'v' must be in upper case 'V' result: %s ",resultline); @@ -9606,58 +9921,62 @@ int decoderesult ( char resultline[], in TKresult[nres]=0; /* Combination for the nresult and the model */ return (0); } - if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */ - printf("ERROR: the number of variable in the resultline, %d, differs from the number of variable used in the model line, %d.\n",j, cptcovs); - fprintf(ficlog,"ERROR: the number of variable in the resultline, %d, differs from the number of variable used in the model line, %d.\n",j, cptcovs); + printf("ERROR: the number of variables in this result line, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs); + fprintf(ficlog,"ERROR: the number of variables in the resultline, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs); } for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */ if(nbocc(resultsav,'=') >1){ - cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' ' - resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */ - cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */ + cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' ' (stra is the rest of the resultline to be analyzed in the next loop *//* resultsav= "V4=1 V5=25.1 V3=0" stra= "V5=25.1 V3=0" strb= "V4=1" */ + cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */ }else cutl(strc,strd,resultsav,'='); - Tvalsel[k]=atof(strc); /* 1 */ + Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */ cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */; - Tvarsel[k]=atoi(strc); + Tvarsel[k]=atoi(strc); /* 4 */ /* Tvarsel is the id of the kth covariate in the result line Tvarsel[1] in "V4=1.." is 4.*/ /* Typevarsel[k]=1; /\* 1 for age product *\/ */ /* cptcovsel++; */ if (nbocc(stra,'=') >0) strcpy(resultsav,stra); /* and analyzes it */ } /* Checking for missing or useless values in comparison of current model needs */ - for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ - if(Typevar[k1]==0){ /* Single covariate in model */ + for(k1=1; k1<= cptcovt ;k1++){ /* Loop on model. model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + if(Typevar[k1]==0){ /* Single covariate in model *//*0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */ match=0; - for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */ - if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */ + for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */ + if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */ modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */ - match=1; + match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */ break; } } if(match == 0){ - printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model); + printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model); + fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model); + return 1; } } } /* Checking for missing or useless values in comparison of current model needs */ - for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */ + for(k2=1; k2 <=j;k2++){ /* Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */ match=0; - for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ if(Typevar[k1]==0){ /* Single */ if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */ - resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */ + resultmodel[k1]=k2; /* k2th variable of the model corresponds to k1 variable of the model. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */ ++match; } } } if(match == 0){ printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model); + fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model); + return 1; }else if(match > 1){ printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model); + fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model); + return 1; } } @@ -9679,7 +9998,7 @@ int decoderesult ( char resultline[], in /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */ /* V5*age V5 known which value for nres? */ /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */ - for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */ + for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* loop on model line */ if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */ k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */ k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */ @@ -9690,8 +10009,8 @@ int decoderesult ( char resultline[], in printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4); k4++;; } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */ - k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */ - k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */ + k3q= resultmodel[k1]; /* resultmodel[1(V5)] = 25.1=k3q */ + k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */ Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */ Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */ Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */ @@ -9714,11 +10033,12 @@ int decodemodel( char model[], int lasto * - cptcovs number of simple covariates * - Tvar[k] is the id of the kth covariate Tvar[1]@12 {1, 2, 3, 8, 10, 11, 8, 3, 7, 8, 5, 6}, thus Tvar[5=V7*V8]=10 * which is a new column after the 9 (ncovcol) variables. - * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual + * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6. * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 . */ +/* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */ { int i, j, k, ks, v; int j1, k1, k2, k3, k4; @@ -9796,12 +10116,12 @@ int decodemodel( char model[], int lasto * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2 * k= 1 2 3 4 5 6 7 8 9 10 11 12 * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8 - * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6} + * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6} * p Tprod[1]@2={ 6, 5} *p Tvard[1][1]@4= {7, 8, 5, 6} * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8 * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2]; - *How to reorganize? + *How to reorganize? Tvars(orted) * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6} * {2, 1, 4, 8, 5, 6, 3, 7} @@ -9826,22 +10146,23 @@ int decodemodel( char model[], int lasto Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0; } cptcovage=0; - for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */ - cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' - modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */ - if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */ + for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */ + cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right + modelsav==V2+V1+V5*age+V4+V3*age strb=V3*age stra=V2+V1V5*age+V4 */ /* "V5+V4+V3+V4*V3+V5*age+V1*age+V1" strb="V5" stra="V4+V3+V4*V3+V5*age+V1*age+V1" */ + if (nbocc(modelsav,'+')==0) + strcpy(strb,modelsav); /* and analyzes it */ /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/ /*scanf("%d",i);*/ - if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */ - cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */ + if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */ + cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */ if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */ /* covar is not filled and then is empty */ cptcovprod--; cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */ - Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */ + Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */ Typevar[k]=1; /* 1 for age product */ - cptcovage++; /* Sums the number of covariates which include age as a product */ - Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */ + cptcovage++; /* Counts the number of covariates which include age as a product */ + Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */ /*printf("stre=%s ", stre);*/ } else if (strcmp(strd,"age")==0) { /* or age*Vn */ cptcovprod--; @@ -9858,12 +10179,13 @@ int decodemodel( char model[], int lasto Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but because this model-covariate is a construction we invent a new column which is after existing variables ncovcol+nqv+ntv+nqtv + k1 - If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2 - Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */ + If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2 + thus after V4 we invent V5 and V6 because age*V3 will be computed in 4 + Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */ Typevar[k]=2; /* 2 for double fixed dummy covariates */ cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */ Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */ - Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */ + Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */ Tvard[k1][1] =atoi(strc); /* m 1 for V1*/ Tvard[k1][2] =atoi(stre); /* n 4 for V4*/ k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */ @@ -9878,7 +10200,7 @@ int decodemodel( char model[], int lasto } } /* End age is not in the model */ } /* End if model includes a product */ - else { /* no more sum */ + else { /* not a product */ /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/ /* scanf("%d",i);*/ cutl(strd,strc,strb,'V'); @@ -9909,7 +10231,7 @@ int decodemodel( char model[], int lasto model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place k = 1 2 3 4 5 6 7 8 9 Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5 - Typevar[k]= 0 0 0 2 1 0 2 1 1 + Typevar[k]= 0 0 0 2 1 0 2 1 0 Fixed[k] 1 1 1 1 3 0 0 or 2 2 3 Dummy[k] 1 0 0 0 3 1 1 2 3 Tmodelind[combination of covar]=k; @@ -9918,11 +10240,11 @@ int decodemodel( char model[], int lasto /* If Tvar[k] >ncovcol it is a product */ /* Tvar[k] is the value n of Vn with n varying for 1 to nvcol, or p Vp=Vn*Vm for product */ /* Computing effective variables, ie used by the model, that is from the cptcovt variables */ - printf("Model=%s\n\ + printf("Model=1+age+%s\n\ Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\ Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\ Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model); - fprintf(ficlog,"Model=%s\n\ + fprintf(ficlog,"Model=1+age+%s\n\ Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\ Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\ Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model); @@ -9989,7 +10311,7 @@ Dummy[k] 0=dummy (0 1), 1 quantitative ( modell[k].subtype= VQ; ncovv++; /* Only simple time varying variables */ nsq++; - TvarsQ[nsq]=Tvar[k]; + TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */ TvarsQind[nsq]=k; TvarV[ncovv]=Tvar[k]; TvarVind[ncovv]=k; /* TvarVind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */ @@ -10921,6 +11243,7 @@ int main(int argc, char *argv[]) double dum=0.; /* Dummy variable */ double ***p3mat; /* double ***mobaverage; */ + double wald; char line[MAXLINE]; char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE]; @@ -10957,7 +11280,8 @@ int main(int argc, char *argv[]) double ftolpl=FTOL; double **prlim; double **bprlim; - double ***param; /* Matrix of parameters */ + double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel) + state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */ double ***paramstart; /* Matrix of starting parameter values */ double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */ double **matcov; /* Matrix of covariance */ @@ -11884,7 +12208,7 @@ Title=%s
        Datafile=%s Firstpass=%d La ", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_")); - fprintf(fichtm,"\n

        Some descriptive statistics

        \n
        Total number of observations=%d
        \n\ + fprintf(fichtm,"\n

        Some descriptive statistics

        \n
        Number of (used) observations=%d
        \n\ Youngest age at first (selected) pass %.2f, oldest age %.2f
        \n\ Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf
        \n",\ imx,agemin,agemax,jmin,jmax,jmean); @@ -12164,48 +12488,130 @@ Please run with mle=-1 to get a correct fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); - printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); + printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */ fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); + + printf("#model= 1 + age "); + fprintf(ficres,"#model= 1 + age "); + fprintf(ficlog,"#model= 1 + age "); + fprintf(fichtm,"\n
        • model=1+age+%s\n \ +
        ", model); + + fprintf(fichtm,"\n\n"); + fprintf(fichtm, ""); + if(nagesqr==1){ + printf(" + age*age "); + fprintf(ficres," + age*age "); + fprintf(ficlog," + age*age "); + fprintf(fichtm, ""); + } + for(j=1;j <=ncovmodel-2;j++){ + if(Typevar[j]==0) { + printf(" + V%d ",Tvar[j]); + fprintf(ficres," + V%d ",Tvar[j]); + fprintf(ficlog," + V%d ",Tvar[j]); + fprintf(fichtm, "",Tvar[j]); + }else if(Typevar[j]==1) { + printf(" + V%d*age ",Tvar[j]); + fprintf(ficres," + V%d*age ",Tvar[j]); + fprintf(ficlog," + V%d*age ",Tvar[j]); + fprintf(fichtm, "",Tvar[j]); + }else if(Typevar[j]==2) { + printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + fprintf(fichtm, "",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + } + } + printf("\n"); + fprintf(ficres,"\n"); + fprintf(ficlog,"\n"); + fprintf(fichtm, ""); + fprintf(fichtm, "\n"); + + for(i=1,jk=1; i <=nlstate; i++){ for(k=1; k <=(nlstate+ndeath); k++){ if (k != i) { + fprintf(fichtm, ""); printf("%d%d ",i,k); fprintf(ficlog,"%d%d ",i,k); fprintf(ficres,"%1d%1d ",i,k); + fprintf(fichtm, "",i,k); for(j=1; j <=ncovmodel; j++){ printf("%12.7f ",p[jk]); fprintf(ficlog,"%12.7f ",p[jk]); fprintf(ficres,"%12.7f ",p[jk]); + fprintf(fichtm, "",p[jk]); jk++; } printf("\n"); fprintf(ficlog,"\n"); fprintf(ficres,"\n"); + fprintf(fichtm, "\n"); } } } + /* fprintf(fichtm,"\n"); */ + fprintf(fichtm,"
        Model=1+ age+ age*age+ V%d+ V%d*age+ V%d*V%d
        %1d%1d%12.7f
        \n"); + fprintf(fichtm, "\n"); + if(mle != 0){ /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */ ftolhess=ftol; /* Usually correct */ hesscov(matcov, hess, p, npar, delti, ftolhess, func); printf("Parameters and 95%% confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W .\n But be careful that parameters are highly correlated because incidence of disability is highly correlated to incidence of recovery.\n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n"); fprintf(ficlog, "Parameters, Wald tests and Wald-based confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W \n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n"); + fprintf(fichtm, "\n

        The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n
        Parameters, Wald tests and Wald-based confidence intervals\n
        W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n
        And Wald-based confidence intervals plus and minus 1.96 * W \n
        It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities and its graphs'.\n
        ",optionfilehtmcov); + fprintf(fichtm,"\n"); + fprintf(fichtm, "\n"); + if(nagesqr==1){ + printf(" + age*age "); + fprintf(ficres," + age*age "); + fprintf(ficlog," + age*age "); + fprintf(fichtm, ""); + } + for(j=1;j <=ncovmodel-2;j++){ + if(Typevar[j]==0) { + printf(" + V%d ",Tvar[j]); + fprintf(fichtm, "",Tvar[j]); + }else if(Typevar[j]==1) { + printf(" + V%d*age ",Tvar[j]); + fprintf(fichtm, "",Tvar[j]); + }else if(Typevar[j]==2) { + fprintf(fichtm, "",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + } + } + fprintf(fichtm, "\n"); + for(i=1,jk=1; i <=nlstate; i++){ for(k=1; k <=(nlstate+ndeath); k++){ if (k != i) { + fprintf(fichtm, ""); printf("%d%d ",i,k); fprintf(ficlog,"%d%d ",i,k); + fprintf(fichtm, "",i,k); for(j=1; j <=ncovmodel; j++){ - printf("%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); - fprintf(ficlog,"%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); + wald=p[jk]/sqrt(matcov[jk][jk]); + printf("%12.7f(%12.7f) sqrt(W)=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); + fprintf(ficlog,"%12.7f(%12.7f) sqrt(W)=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); + if(fabs(wald) > 1.96){ + fprintf(fichtm, "", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); jk++; } printf("\n"); fprintf(ficlog,"\n"); + fprintf(fichtm, "\n"); } } } } /* end of hesscov and Wald tests */ + fprintf(fichtm,"
        Model=1+ age+ age*age+ V%d+ V%d*age+ V%d*V%d
        %1d%1d%12.7f
        (%12.7f)
        ",p[jk],sqrt(matcov[jk][jk])); + }else{ + fprintf(fichtm, "        		%12.7f (%12.7f)
        ",p[jk],sqrt(matcov[jk][jk])); + } + fprintf(fichtm,"sqrt(W)=%8.3f
        ",wald); + fprintf(fichtm,"[%12.7f;%12.7f]
        \n"); /* */ fprintf(ficres,"# Scales (for hessian or gradient estimation)\n"); @@ -12417,11 +12823,13 @@ Please run with mle=-1 to get a correct } /* Results */ + endishere=0; nresult=0; + parameterline=0; do{ if(!fgets(line, MAXLINE, ficpar)){ endishere=1; - parameterline=14; + parameterline=15; }else if (line[0] == '#') { /* If line starts with a # it is a comment */ numlinepar++; @@ -12434,12 +12842,13 @@ Please run with mle=-1 to get a correct parameterline=11; else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp)) parameterline=12; - else if(sscanf(line,"result:%[^\n]\n",modeltemp)) + else if(sscanf(line,"result:%[^\n]\n",modeltemp)){ parameterline=13; + } else{ parameterline=14; } - switch (parameterline){ + switch (parameterline){ /* =0 only if only comments */ case 11: if((num_filled=sscanf(line,"prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d\n",&prevfcast,&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2,&mobilavproj)) !=EOF && (num_filled == 8)){ fprintf(ficparo,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj); @@ -12452,9 +12861,9 @@ Please run with mle=-1 to get a correct prvforecast = 1; } else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/ - printf("prevforecast=%d yearsfproj=%lf.2 mobil_average=%d\n",prevfcast,yrfproj,mobilavproj); - fprintf(ficlog,"prevforecast=%d yearsfproj=%lf.2 mobil_average=%d\n",prevfcast,yrfproj,mobilavproj); - fprintf(ficres,"prevforecast=%d yearsfproj=%lf.2 mobil_average=%d\n",prevfcast,yrfproj,mobilavproj); + printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj); + fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj); + fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj); prvforecast = 2; } else { @@ -12475,9 +12884,9 @@ Please run with mle=-1 to get a correct prvbackcast = 1; } else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/ - printf("prevbackcast=%d yearsbproj=%lf.2 mobil_average=%d\n",prevbcast,yrbproj,mobilavproj); - fprintf(ficlog,"prevbackcast=%d yearsbproj=%lf.2 mobil_average=%d\n",prevbcast,yrbproj,mobilavproj); - fprintf(ficres,"prevbackcast=%d yearsbproj=%lf.2 mobil_average=%d\n",prevbcast,yrbproj,mobilavproj); + printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj); + fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj); + fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj); prvbackcast = 2; } else { @@ -12487,41 +12896,41 @@ Please run with mle=-1 to get a correct } break; case 13: - if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){ - if (num_filled == 0){ - resultline[0]='\0'; - printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line); - fprintf(ficlog,"Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line); - break; - } else if (num_filled != 1){ - printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line); - fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line); - } - nresult++; /* Sum of resultlines */ - printf("Result %d: result=%s\n",nresult, resultline); - if(nresult > MAXRESULTLINES){ - printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult); - fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult); - goto end; - } - decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */ + num_filled=sscanf(line,"result:%[^\n]\n",resultline); + nresult++; /* Sum of resultlines */ + printf("Result %d: result:%s\n",nresult, resultline); + if(nresult > MAXRESULTLINESPONE-1){ + printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres); + fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres); + goto end; + } + if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */ fprintf(ficparo,"result: %s\n",resultline); fprintf(ficres,"result: %s\n",resultline); fprintf(ficlog,"result: %s\n",resultline); - break; - case 14: - printf("Error: Unknown command '%s'\n",line); - fprintf(ficlog,"Error: Unknown command '%s'\n",line); - if(ncovmodel >=2 && nresult==0 ){ - printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line); - fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line); - } - /* goto end; */ - break; - default: - nresult=1; - decoderesult(".",nresult ); /* No covariate */ + } else + goto end; + break; + case 14: + printf("Error: Unknown command '%s'\n",line); + fprintf(ficlog,"Error: Unknown command '%s'\n",line); + if(line[0] == ' ' || line[0] == '\n'){ + printf("It should not be an empty line '%s'\n",line); + fprintf(ficlog,"It should not be an empty line '%s'\n",line); + } + if(ncovmodel >=2 && nresult==0 ){ + printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line); + fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line); } + /* goto end; */ + break; + case 15: + printf("End of resultlines.\n"); + fprintf(ficlog,"End of resultlines.\n"); + break; + default: /* parameterline =0 */ + nresult=1; + decoderesult(".",nresult ); /* No covariate */ } /* End switch parameterline */ }while(endishere==0); /* End do */ @@ -12793,9 +13202,9 @@ Please run with mle=-1 to get a correct for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */ if(i1 != 1 && TKresult[nres]!= k) continue; - printf("\n#****** Result for:"); - fprintf(ficrest,"\n#****** Result for:"); - fprintf(ficlog,"\n#****** Result for:"); + printf("\n# model %s \n#****** Result for:", model); + fprintf(ficrest,"\n# model %s \n#****** Result for:", model); + fprintf(ficlog,"\n# model %s \n#****** Result for:", model); for(j=1;j<=cptcoveff;j++){ printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);