version 1.320, 2022/06/02 05:10:11
|
version 1.322, 2022/07/22 12:27:48
|
Line 1
|
Line 1
|
/* $Id$ |
/* $Id$ |
$State$ |
$State$ |
$Log$ |
$Log$ |
|
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 |
Revision 1.320 2022/06/02 05:10:11 brouard |
*** empty log message *** |
*** empty log message *** |
|
|
Line 7240 void printinghtml(char fileresu[], char
|
Line 7248 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 7427 See page 'Matrix of variance-covariance
|
Line 7435 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 7563 void printinggnuplot(char fileresu[], ch
|
Line 7571 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 12551 Please run with mle=-1 to get a correct
|
Line 12559 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>The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n</br>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 '<a href=\"%s\">Matrix of variance-covariance of one-step probabilities and its graphs</a>'.\n</br>",optionfilehtmcov); |
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 12581 Please run with mle=-1 to get a correct
|
Line 12590 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 13191 Please run with mle=-1 to get a correct
|
Line 13199 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)]); |