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Diff for /imach/src/imach.c between versions 1.319 and 1.321

version 1.319, 2022/06/02 04:45:11 version 1.321, 2022/07/22 12:04:24
Line 1 Line 1
 /* $Id$  /* $Id$
   $State$    $State$
   $Log$    $Log$
     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    Revision 1.319  2022/06/02 04:45:11  brouard
   * imach.c (Module): Adding the Wald tests from the log to the main    * imach.c (Module): Adding the Wald tests from the log to the main
   htm for better display of the maximum likelihood estimators.    htm for better display of the maximum likelihood estimators.
Line 1422  int **nbcode, *Tvar; /**< model=V2 => Tv Line 1430  int **nbcode, *Tvar; /**< model=V2 => Tv
 /* Tage[cptcovage]=k            5               8      */ /* Position in the model of ith cov*age */  /* 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 */  /* 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 */  /* 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)  */  /* TvarFind;  TvarFind[1]=6,  TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod)  */
 /* Type                    */  /* Type                    */
 /* V         1  2  3  4  5 */  /* V         1  2  3  4  5 */
 /*           F  F  V  V  V */  /*           F  F  V  V  V */
Line 3645  double func( double *x) Line 3653  double func( double *x)
         /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */          /* # 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 */          /*             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 */          /*  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)  */          /* 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)*/          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 */          /* V1*V2 (7)  TvarFind[2]=7, TvarFind[3]=9 */
       }        }
Line 6118  void  concatwav(int wav[], int **dh, int Line 6126  void  concatwav(int wav[], int **dh, int
             varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;              varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
       }        }
     }      }
     if((int)age ==50){      /* if((int)age ==50){ */
       printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]);      /*   printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
     }      /* } */
     /* Computing expectancies */      /* Computing expectancies */
     hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);        hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);  
     for(i=1; i<=nlstate;i++)      for(i=1; i<=nlstate;i++)
Line 7237  void printinghtml(char fileresu[], char Line 7245  void printinghtml(char fileresu[], char
       }        }
                 
        /* if(nqfveff+nqtveff 0) */ /* Test to be done */         /* if(nqfveff+nqtveff 0) */ /* Test to be done */
        fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");         fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
        if(invalidvarcomb[k1]){         if(invalidvarcomb[k1]){
          fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);            fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1); 
          printf("\nCombination (%d) ignored because no cases \n",k1);            printf("\nCombination (%d) ignored because no cases \n",k1); 
Line 7424  See page 'Matrix of variance-covariance Line 7432  See page 'Matrix of variance-covariance
         fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);          fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
       }        }
   
        fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");         fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
   
        if(invalidvarcomb[k1]){         if(invalidvarcomb[k1]){
          fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);            fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1); 
Line 7560  void printinggnuplot(char fileresu[], ch Line 7568  void printinggnuplot(char fileresu[], ch
         fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);          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,"\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 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_"),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); */          /* 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*/        /* k1-1 error should be nres-1*/
Line 12548  Please run with mle=-1 to get a correct Line 12556  Please run with mle=-1 to get a correct
       hesscov(matcov, hess, p, npar, delti, ftolhess, func);        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");        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(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<p>Parameters, Wald tests and Wald-based confidence intervals\n</br> W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n</br> And Wald-based confidence intervals plus and minus 1.96 * W \n </br> It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n</br>");
       fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");        fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
       fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");        fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
       if(nagesqr==1){        if(nagesqr==1){
Line 12578  Please run with mle=-1 to get a correct Line 12587  Please run with mle=-1 to get a correct
             fprintf(fichtm, "<td>%1d%1d</td>",i,k);              fprintf(fichtm, "<td>%1d%1d</td>",i,k);
             for(j=1; j <=ncovmodel; j++){              for(j=1; j <=ncovmodel; j++){
               wald=p[jk]/sqrt(matcov[jk][jk]);                wald=p[jk]/sqrt(matcov[jk][jk]);
               printf("%12.7f(%12.7f) 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]));                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) 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){                if(fabs(wald) > 1.96){
                 fprintf(fichtm, "<td><b>%12.7f</b> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));                  fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
                 fprintf(fichtm,"<b>W=%8.3f</b></br>",wald);  
               }else{                }else{
                 fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));                  fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
                 fprintf(fichtm,"W=%8.3f</br>",wald);  
               }                }
                 fprintf(fichtm,"sqrt(W)=%8.3f</br>",wald);
               fprintf(fichtm,"[%12.7f;%12.7f]</br></td>", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));                fprintf(fichtm,"[%12.7f;%12.7f]</br></td>", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
               jk++;                 jk++; 
             }              }
Line 13188  Please run with mle=-1 to get a correct Line 13196  Please run with mle=-1 to get a correct
     for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */      for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
       if(i1 != 1 && TKresult[nres]!= k)        if(i1 != 1 && TKresult[nres]!= k)
         continue;          continue;
       printf("\n#****** Result for:");        printf("\n# model %s \n#****** Result for:", model);
       fprintf(ficrest,"\n#****** Result for:");        fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
       fprintf(ficlog,"\n#****** Result for:");        fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
       for(j=1;j<=cptcoveff;j++){         for(j=1;j<=cptcoveff;j++){ 
         printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,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)]);          fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
Removed from v.1.319  
changed lines
  Added in v.1.321

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