Datafile=%s Firstpass=%d La
}/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
} /* end j==0 */
/* bool =0 we keep that guy which corresponds to the combination of dummy values */
- if(bool==1){
+ if(bool==1){ /*Selected */
/* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
and mw[mi+1][iind]. dh depends on stepm. */
agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
@@ -4572,16 +4583,16 @@ 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 */
+ }
/* 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); */
/* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
freq[s[m][iind]][s[m+1][iind]][iagemax+3] += weight[iind]; /* Total is in iagemax+3 *//* At age of beginning of transition, where status is known */
}
- for (z1=1; z1<= nqfveff; z1++) {
- idq[z1]++;
- meanq[z1]+=covar[ncovcol+z1][iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
- /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
- }
} /* end if between passes */
if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
dateintsum=dateintsum+k2; /* on all covariates ?*/
@@ -4592,6 +4603,11 @@ Title=%s
Datafile=%s Firstpass=%d La
bool=1;
}/* end bool 2 */
} /* end m */
+ /* 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 *\/ */
+ /* } */
} /* end bool */
} /* end iind = 1 to imx */
/* prop[s][age] is feeded for any initial and valid live state as well as
@@ -4629,18 +4645,26 @@ Title=%s
Datafile=%s Firstpass=%d La
fprintf(ficresphtmfr, "**********\n");
fprintf(ficlog, "**********\n");
}
- /*
- Printing means of quantitative variables if any
- */
- for (z1=1; z1<= nqfveff; z1++) {
- fprintf(ficresphtmfr,"V quantitative id %d, number of idividuals= %f, sum=%f", z1, idq[z1], meanq[z1]);
- fprintf(ficresphtmfr,", mean=%f\n",meanq[z1]/idq[z1]);
- }
- /* for (z1=1; z1<= nqtveff; z1++) { */
- /* for(m=1;m<=lastpass;m++){ */
- /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f
\n", z1, m, meanqt[m][z1]); */
- /* } */
- /* } */
+ /*
+ 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=%.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]));
+ }
+ /* for (z1=1; z1<= nqtveff; z1++) { */
+ /* for(m=1;m<=lastpass;m++){ */
+ /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f
\n", z1, m, meanqt[m][z1]); */
+ /* } */
+ /* } */
fprintf(ficresphtm,"
");
if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
@@ -4876,7 +4900,7 @@ Title=%s
Datafile=%s Firstpass=%d La
fprintf(ficlog,"\n");
}
}
- }
+ } /* end of state i */
printf("#Freqsummary\n");
fprintf(ficlog,"\n");
for(s1=-1; s1 <=nlstate+ndeath; s1++){
@@ -4924,6 +4948,7 @@ Title=%s
Datafile=%s Firstpass=%d La
fclose(ficresphtmfr);
free_vector(idq,1,nqfveff);
free_vector(meanq,1,nqfveff);
+ free_vector(stdq,1,nqfveff);
free_matrix(meanqt,1,lastpass,1,nqtveff);
free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
@@ -5339,9 +5364,11 @@ void concatwav(int wav[], int **dh, int
/* *cptcov=0; */
for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
+ for (k=1; k <= maxncov; k++)
+ for(j=1; j<=2; j++)
+ nbcode[k][j]=0; /* Valgrind */
/* Loop on covariates without age and products and no quantitative variable */
- /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
for (j=-1; (j < maxncov); j++) Ndum[j]=0;
if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
@@ -5359,7 +5386,11 @@ void concatwav(int wav[], int **dh, int
modmaxcovj=ij;
else if (ij < modmincovj)
modmincovj=ij;
- if ((ij < -1) && (ij > NCOVMAX)){
+ if (ij <0 || ij >1 ){
+ 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);
+ }
+ if ((ij < -1) || (ij > NCOVMAX)){
printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
exit(1);
}else
@@ -5405,12 +5436,18 @@ void concatwav(int wav[], int **dh, int
/* nbcode[Tvar[j]][3]=2; */
/* To be continued (not working yet). */
ij=0; /* ij is similar to i but can jump over null modalities */
- for (i=modmincovj; i<=modmaxcovj; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
+
+ /* for (i=modmincovj; i<=modmaxcovj; i++) { */ /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
+ /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
+ /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
+ * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
+ /*, could be restored in the future */
+ for (i=0; i<=1; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
if (Ndum[i] == 0) { /* If nobody responded to this modality k */
break;
}
ij++;
- nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1*/
+ nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1 . Could be -1*/
cptcode = ij; /* New max modality for covar j */
} /* end of loop on modality i=-1 to 1 or more */
break;
@@ -5426,21 +5463,7 @@ void concatwav(int wav[], int **dh, int
break;
} /* end switch */
} /* end dummy test */
-
- /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
- /* /\*recode from 0 *\/ */
- /* k is a modality. If we have model=V1+V1*sex */
- /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
- /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
- /* } */
- /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
- /* if (ij > ncodemax[j]) { */
- /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
- /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
- /* break; */
- /* } */
- /* } /\* end of loop on modality k *\/ */
- } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
+ } /* 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;
/* Look at fixed dummy (single or product) covariates to check empty modalities */
@@ -9714,7 +9737,7 @@ Dummy[k] 0=dummy (0 1), 1 quantitative (
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);
- for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
+ for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0;k<=cptcovt; k++){ /* or cptocvt */
if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
Fixed[k]= 0;
@@ -9964,11 +9987,12 @@ Dummy[k] 0=dummy (0 1), 1 quantitative (
/* Searching for doublons in the model */
for(k1=1; k1<= cptcovt;k1++){
for(k2=1; k2 maxwav){
+ printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
+ fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
+ fflush(ficlog);
+ goto end;
+ }
+ printf("ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
fprintf(ficparo,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
- fprintf(ficres,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
+ fprintf(ficres,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, 0, weightopt);
fprintf(ficlog,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
}
/* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
@@ -11614,7 +11644,7 @@ Title=%s
Datafile=%s Firstpass=%d La
firstpass, lastpass, stepm, weightopt, model);
fprintf(fichtm,"\n");
- fprintf(fichtm,"Parameter line 2
- Tolerance for the convergence of the likelihood: ftol=%f \n
- Interval for the elementary matrix (in month): stepm=%d",\
+ fprintf(fichtm,"
Parameter line 2
- Tolerance for the convergence of the likelihood: ftol=%g \n
- Interval for the elementary matrix (in month): stepm=%d",\
ftol, stepm);
fprintf(fichtm,"\n
- Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
ncurrv=1;