--- imach/src/imach.c 2016/07/12 08:40:03 1.225 +++ imach/src/imach.c 2016/07/12 18:42:34 1.226 @@ -1,6 +1,9 @@ -/* $Id: imach.c,v 1.225 2016/07/12 08:40:03 brouard Exp $ +/* $Id: imach.c,v 1.226 2016/07/12 18:42:34 brouard Exp $ $State: Exp $ $Log: imach.c,v $ + Revision 1.226 2016/07/12 18:42:34 brouard + Summary: temp + Revision 1.225 2016/07/12 08:40:03 brouard Summary: saving but not running @@ -689,8 +692,25 @@ Back prevalence and projections: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying nhstepm*hstepm matrices. Returns p3mat[i][j][h] after calling p3mat[i][j][h]=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ - 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); + 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); + +Important routines + +- func (or funcone), computes logit (pij) distinguishing + o fixed variables (single or product dummies or quantitative); + o varying variables by: + (1) wave (single, product dummies, quantitative), + (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be: + % fixed dummy (treated) or quantitative (not done because time-consuming); + % varying dummy (not done) or quantitative (not done); +- Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities) + and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually. +- printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables + o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if + race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless. + + Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr). Institut national d'études démographiques, Paris. This software have been partly granted by Euro-REVES, a concerted action @@ -761,6 +781,7 @@ Back prevalence and projections: #include #include #include +#include #ifdef _WIN32 #include @@ -843,12 +864,12 @@ typedef struct { #define ODIRSEPARATOR '\\' #endif -/* $Id: imach.c,v 1.225 2016/07/12 08:40:03 brouard Exp $ */ +/* $Id: imach.c,v 1.226 2016/07/12 18:42:34 brouard Exp $ */ /* $State: Exp $ */ #include "version.h" char version[]=__IMACH_VERSION__; char copyright[]="February 2016,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2018"; -char fullversion[]="$Revision: 1.225 $ $Date: 2016/07/12 08:40:03 $"; +char fullversion[]="$Revision: 1.226 $ $Date: 2016/07/12 18:42:34 $"; char strstart[80]; char optionfilext[10], optionfilefiname[FILENAMELENGTH]; int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */ @@ -1015,7 +1036,9 @@ double ***cotvar; /* Time varying covari double ***cotqvar; /* Time varying quantitative covariate itqv */ double idx; int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */ -int *Typevar; /**< 1 for qualitative fixed, 2 for quantitative fixed, 3 for qualitive varying, 4 for quanti varying*/ +int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */ +int *Fixed; /** Fixed[Tvar[k]] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */ +int *Dummy; /** Dummy[Tvar[k]] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */ int *Tage; int *Ndum; /** Freq of modality (tricode */ /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */ @@ -2890,145 +2913,145 @@ double ***hbxij(double ***po, int nhstep /*************** log-likelihood *************/ double func( double *x) { - int i, ii, j, k, mi, d, kk; - int ioffset=0; - double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1]; - double **out; - double sw; /* Sum of weights */ - double lli; /* Individual log likelihood */ - int s1, s2; - int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quatitative time varying covariate */ - double bbh, survp; - long ipmx; - double agexact; - /*extern weight */ - /* We are differentiating ll according to initial status */ - /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/ - /*for(i=1;i 1 the results are less biased than in previous versions. - */ - s1=s[mw[mi][i]][i]; - s2=s[mw[mi+1][i]][i]; - bbh=(double)bh[mi][i]/(double)stepm; - /* bias bh is positive if real duration - * is higher than the multiple of stepm and negative otherwise. - */ - /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/ - if( s2 > nlstate){ - /* i.e. if s2 is a death state and if the date of death is known - then the contribution to the likelihood is the probability to - die between last step unit time and current step unit time, - which is also equal to probability to die before dh - minus probability to die before dh-stepm . - In version up to 0.92 likelihood was computed - as if date of death was unknown. Death was treated as any other - health state: the date of the interview describes the actual state - and not the date of a change in health state. The former idea was - to consider that at each interview the state was recorded - (healthy, disable or death) and IMaCh was corrected; but when we - introduced the exact date of death then we should have modified - the contribution of an exact death to the likelihood. This new - contribution is smaller and very dependent of the step unit - stepm. It is no more the probability to die between last interview - and month of death but the probability to survive from last - interview up to one month before death multiplied by the - probability to die within a month. Thanks to Chris - Jackson for correcting this bug. Former versions increased - mortality artificially. The bad side is that we add another loop - which slows down the processing. The difference can be up to 10% - lower mortality. - */ - /* If, at the beginning of the maximization mostly, the - cumulative probability or probability to be dead is - constant (ie = 1) over time d, the difference is equal to - 0. out[s1][3] = savm[s1][3]: probability, being at state - s1 at precedent wave, to be dead a month before current - wave is equal to probability, being at state s1 at - precedent wave, to be dead at mont of the current - wave. Then the observed probability (that this person died) - is null according to current estimated parameter. In fact, - it should be very low but not zero otherwise the log go to - infinity. - */ + /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */ + /* But now since version 0.9 we anticipate for bias at large stepm. + * If stepm is larger than one month (smallest stepm) and if the exact delay + * (in months) between two waves is not a multiple of stepm, we rounded to + * the nearest (and in case of equal distance, to the lowest) interval but now + * we keep into memory the bias bh[mi][i] and also the previous matrix product + * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the + * probability in order to take into account the bias as a fraction of the way + * from savm to out if bh is negative or even beyond if bh is positive. bh varies + * -stepm/2 to stepm/2 . + * For stepm=1 the results are the same as for previous versions of Imach. + * For stepm > 1 the results are less biased than in previous versions. + */ + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + bbh=(double)bh[mi][i]/(double)stepm; + /* bias bh is positive if real duration + * is higher than the multiple of stepm and negative otherwise. + */ + /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/ + if( s2 > nlstate){ + /* i.e. if s2 is a death state and if the date of death is known + then the contribution to the likelihood is the probability to + die between last step unit time and current step unit time, + which is also equal to probability to die before dh + minus probability to die before dh-stepm . + In version up to 0.92 likelihood was computed + as if date of death was unknown. Death was treated as any other + health state: the date of the interview describes the actual state + and not the date of a change in health state. The former idea was + to consider that at each interview the state was recorded + (healthy, disable or death) and IMaCh was corrected; but when we + introduced the exact date of death then we should have modified + the contribution of an exact death to the likelihood. This new + contribution is smaller and very dependent of the step unit + stepm. It is no more the probability to die between last interview + and month of death but the probability to survive from last + interview up to one month before death multiplied by the + probability to die within a month. Thanks to Chris + Jackson for correcting this bug. Former versions increased + mortality artificially. The bad side is that we add another loop + which slows down the processing. The difference can be up to 10% + lower mortality. + */ + /* If, at the beginning of the maximization mostly, the + cumulative probability or probability to be dead is + constant (ie = 1) over time d, the difference is equal to + 0. out[s1][3] = savm[s1][3]: probability, being at state + s1 at precedent wave, to be dead a month before current + wave is equal to probability, being at state s1 at + precedent wave, to be dead at mont of the current + wave. Then the observed probability (that this person died) + is null according to current estimated parameter. In fact, + it should be very low but not zero otherwise the log go to + infinity. + */ /* #ifdef INFINITYORIGINAL */ /* lli=log(out[s1][s2] - savm[s1][s2]); */ /* #else */ @@ -3037,187 +3060,187 @@ double func( double *x) /* else */ /* lli=log(out[s1][s2] - savm[s1][s2]); */ /* #endif */ - lli=log(out[s1][s2] - savm[s1][s2]); + lli=log(out[s1][s2] - savm[s1][s2]); - } else if ( s2==-1 ) { /* alive */ - for (j=1,survp=0. ; j<=nlstate; j++) - survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; - /*survp += out[s1][j]; */ - lli= log(survp); - } - else if (s2==-4) { - for (j=3,survp=0. ; j<=nlstate; j++) - survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; - lli= log(survp); - } - else if (s2==-5) { - for (j=1,survp=0. ; j<=2; j++) - survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; - lli= log(survp); - } - else{ - lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */ - /* lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2]));*/ /* linear interpolation */ - } - /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/ - /*if(lli ==000.0)*/ - /*printf("bbh= %f lli=%f savm=%f out=%f %d\n",bbh,lli,savm[s1][s2], out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]],i); */ - ipmx +=1; - sw += weight[i]; - ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; - /* if (lli < log(mytinydouble)){ */ - /* printf("Close to inf lli = %.10lf < %.10lf i= %d mi= %d, s[%d][i]=%d s1=%d s2=%d\n", lli,log(mytinydouble), i, mi,mw[mi][i], s[mw[mi][i]][i], s1,s2); */ - /* fprintf(ficlog,"Close to inf lli = %.10lf i= %d mi= %d, s[mw[mi][i]][i]=%d\n", lli, i, mi,s[mw[mi][i]][i]); */ - /* } */ - } /* end of wave */ - } /* 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]; - for(mi=1; mi<= wav[i]-1; mi++){ - for (ii=1;ii<=nlstate+ndeath;ii++) - for (j=1;j<=nlstate+ndeath;j++){ - oldm[ii][j]=(ii==j ? 1.0 : 0.0); - savm[ii][j]=(ii==j ? 1.0 : 0.0); - } - for(d=0; d<=dh[mi][i]; d++){ - newm=savm; - agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; - cov[2]=agexact; - if(nagesqr==1) - cov[3]= agexact*agexact; - for (kk=1; kk<=cptcovage;kk++) { - cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; - } - out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, - 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); - savm=oldm; - oldm=newm; - } /* end mult */ - - s1=s[mw[mi][i]][i]; - s2=s[mw[mi+1][i]][i]; - bbh=(double)bh[mi][i]/(double)stepm; - lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2])); /* linear interpolation */ - ipmx +=1; - sw += weight[i]; - ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; - } /* end of wave */ - } /* end of individual */ - } else if(mle==3){ /* exponential inter-extrapolation */ - for (i=1,ipmx=0, sw=0.; i<=imx; i++){ - for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; - for(mi=1; mi<= wav[i]-1; mi++){ - for (ii=1;ii<=nlstate+ndeath;ii++) - for (j=1;j<=nlstate+ndeath;j++){ - oldm[ii][j]=(ii==j ? 1.0 : 0.0); - savm[ii][j]=(ii==j ? 1.0 : 0.0); - } - for(d=0; d1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */ - ipmx +=1; - sw += weight[i]; - ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; - } /* end of wave */ - } /* end of individual */ - }else if (mle==4){ /* ml=4 no inter-extrapolation */ - for (i=1,ipmx=0, sw=0.; i<=imx; i++){ - for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; - for(mi=1; mi<= wav[i]-1; mi++){ - for (ii=1;ii<=nlstate+ndeath;ii++) - for (j=1;j<=nlstate+ndeath;j++){ - oldm[ii][j]=(ii==j ? 1.0 : 0.0); - savm[ii][j]=(ii==j ? 1.0 : 0.0); - } - for(d=0; d(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2]));*/ /* linear interpolation */ + } + /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/ + /*if(lli ==000.0)*/ + /*printf("bbh= %f lli=%f savm=%f out=%f %d\n",bbh,lli,savm[s1][s2], out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]],i); */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + /* if (lli < log(mytinydouble)){ */ + /* printf("Close to inf lli = %.10lf < %.10lf i= %d mi= %d, s[%d][i]=%d s1=%d s2=%d\n", lli,log(mytinydouble), i, mi,mw[mi][i], s[mw[mi][i]][i], s1,s2); */ + /* fprintf(ficlog,"Close to inf lli = %.10lf i= %d mi= %d, s[mw[mi][i]][i]=%d\n", lli, i, mi,s[mw[mi][i]][i]); */ + /* } */ + } /* end of wave */ + } /* 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]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d<=dh[mi][i]; d++){ + newm=savm; + agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; + for (kk=1; kk<=cptcovage;kk++) { + cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; + } + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); + savm=oldm; + oldm=newm; + } /* end mult */ + + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + bbh=(double)bh[mi][i]/(double)stepm; + lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2])); /* linear interpolation */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + } /* end of wave */ + } /* end of individual */ + } else if(mle==3){ /* exponential inter-extrapolation */ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + } /* end of wave */ + } /* end of individual */ + }else if (mle==4){ /* ml=4 no inter-extrapolation */ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d nlstate){ - lli=log(out[s1][s2] - savm[s1][s2]); - } else if ( s2==-1 ) { /* alive */ - for (j=1,survp=0. ; j<=nlstate; j++) - survp += out[s1][j]; - lli= log(survp); - }else{ - lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */ - } - ipmx +=1; - sw += weight[i]; - ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); + savm=oldm; + oldm=newm; + } /* end mult */ + + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + if( s2 > nlstate){ + lli=log(out[s1][s2] - savm[s1][s2]); + } else if ( s2==-1 ) { /* alive */ + for (j=1,survp=0. ; j<=nlstate; j++) + survp += out[s1][j]; + lli= log(survp); + }else{ + lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */ + } + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; /* printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]); */ - } /* end of wave */ - } /* end of individual */ - }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */ - for (i=1,ipmx=0, sw=0.; i<=imx; i++){ - for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; - for(mi=1; mi<= wav[i]-1; mi++){ - for (ii=1;ii<=nlstate+ndeath;ii++) - for (j=1;j<=nlstate+ndeath;j++){ - oldm[ii][j]=(ii==j ? 1.0 : 0.0); - savm[ii][j]=(ii==j ? 1.0 : 0.0); - } - for(d=0; d\nIMaCh PHTM_ %s\n %s
%s \ + strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm")); + if((ficresphtm=fopen(fileresphtm,"w"))==NULL) { + printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno)); + fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno)); + fflush(ficlog); + exit(70); + } + else{ + fprintf(ficresphtm,"\nIMaCh PHTM_ %s\n %s
%s \
\n\ 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

\n",fileresphtm, fileresphtm); + 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

\n",fileresphtm, fileresphtm); - strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm")); - if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) { - printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno)); - fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno)); - fflush(ficlog); - exit(70); - } - else{ - fprintf(ficresphtmfr,"\nIMaCh PHTM_Frequency table %s\n %s
%s \ + strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm")); + if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) { + printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno)); + fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno)); + fflush(ficlog); + exit(70); + } + else{ + fprintf(ficresphtmfr,"\nIMaCh PHTM_Frequency table %s\n %s
%s \
\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 by age at begin of transition

Unknown status is -1
\n",fileresphtmfr, fileresphtmfr); + fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); + } + fprintf(ficresphtmfr,"Current page is file %s
\n\n

Frequencies of all effective transitions by age at begin of transition

Unknown status is -1
\n",fileresphtmfr, fileresphtmfr); - freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+3+AGEMARGE); - j1=0; + freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+3+AGEMARGE); + j1=0; - j=ncoveff; - if (cptcovn<1) {j=1;ncodemax[1]=1;} + j=ncoveff; + if (cptcovn<1) {j=1;ncodemax[1]=1;} - first=1; + first=1; - /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels: - reference=low_education V1=0,V2=0 - med_educ V1=1 V2=0, - high_educ V1=0 V2=1 - Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff - */ + /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels: + reference=low_education V1=0,V2=0 + med_educ V1=1 V2=0, + high_educ V1=0 V2=1 + Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff + */ - for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on covariates combination excluding varying and quantitatives */ - posproptt=0.; - /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]); - scanf("%d", i);*/ - for (i=-5; i<=nlstate+ndeath; i++) - for (jk=-5; jk<=nlstate+ndeath; jk++) - for(m=iagemin; m <= iagemax+3; m++) - freq[i][jk][m]=0; - - for (i=1; i<=nlstate; i++) { - for(m=iagemin; m <= iagemax+3; m++) - prop[i][m]=0; - posprop[i]=0; - pospropt[i]=0; - } - for (z1=1; z1<= nqfveff; z1++) { - meanq[z1]+=0.; - for(m=1;m<=lastpass;m++){ - meanqt[m][z1]=0.; - } - } - - dateintsum=0; - k2cpt=0; - /* For that comination of covariate j1, we count and print the frequencies */ - for (iind=1; iind<=imx; iind++) { /* For each individual iind */ - bool=1; - if (nqfveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */ - for (z1=1; z1<= nqfveff; z1++) { - meanq[z1]+=coqvar[Tvar[z1]][iind]; - } - for (z1=1; z1<=ncoveff; z1++) { - /* if(Tvaraff[z1] ==-20){ */ - /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */ - /* }else if(Tvaraff[z1] ==-10){ */ - /* /\* sumnew+=coqvar[z1][iind]; *\/ */ - /* }else */ - if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ - /* Tests if this individual i responded to j1 (V4=1 V3=0) */ - bool=0; - /* printf("bool=%d i=%d, z1=%d, Tvaraff[%d]=%d, covar[Tvarff][%d]=%2f, codtabm(%d,%d)=%d, nbcode[Tvaraff][codtabm(%d,%d)=%d, j1=%d\n", - bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1), - j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/ - /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/ - } - } /* end z1 */ - } /* cptcovn > 0 */ - - if (bool==1){ /* We selected an individual iin satisfying combination j1 */ - /* for(m=firstpass; m<=lastpass; m++){ */ - for(mi=1; mi=firstpass && m <=lastpass){ - k2=anint[m][iind]+(mint[m][iind]/12.); - /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/ - if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */ - if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */ - if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */ - prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */ - if (m1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99)) { - dateintsum=dateintsum+k2; - k2cpt++; - /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */ - } - /*}*/ - } /* end m */ - } /* end bool */ - } /* end iind = 1 to imx */ - /* prop[s][age] is feeded 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 */ - - - /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/ - pstamp(ficresp); - if (ncoveff>0) { - fprintf(ficresp, "\n#********** Variable "); - fprintf(ficresphtm, "\n

********** Variable "); - fprintf(ficresphtmfr, "\n

********** Variable "); - for (z1=1; z1<=ncoveff; z1++){ - fprintf(ficresp, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); - fprintf(ficresphtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); - fprintf(ficresphtmfr, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); - } - fprintf(ficresp, "**********\n#"); - fprintf(ficresphtm, "**********

\n"); - fprintf(ficresphtmfr, "**********\n"); - fprintf(ficlog, "\n#********** Variable "); - for (z1=1; z1<=ncoveff; z1++) fprintf(ficlog, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); - fprintf(ficlog, "**********\n"); - } - fprintf(ficresphtm,""); - for(i=1; i<=nlstate;i++) { - fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i); - fprintf(ficresphtm, "",i,i); - } - fprintf(ficresp, "\n"); - fprintf(ficresphtm, "\n"); - - /* Header of frequency table by age */ - fprintf(ficresphtmfr,"
AgePrev(%d)N(%d)N
"); - fprintf(ficresphtmfr," "); - for(jk=-1; jk <=nlstate+ndeath; jk++){ - for(m=-1; m <=nlstate+ndeath; m++){ - if(jk!=0 && m!=0) - fprintf(ficresphtmfr," ",jk,m); - } - } - fprintf(ficresphtmfr, "\n"); + for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on covariates combination excluding varying and quantitatives */ + posproptt=0.; + /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]); + scanf("%d", i);*/ + for (i=-5; i<=nlstate+ndeath; i++) + for (jk=-5; jk<=nlstate+ndeath; jk++) + for(m=iagemin; m <= iagemax+3; m++) + freq[i][jk][m]=0; + + for (i=1; i<=nlstate; i++) { + for(m=iagemin; m <= iagemax+3; m++) + prop[i][m]=0; + posprop[i]=0; + pospropt[i]=0; + } + for (z1=1; z1<= nqfveff; z1++) { + meanq[z1]+=0.; + for(m=1;m<=lastpass;m++){ + meanqt[m][z1]=0.; + } + } - /* For each age */ - for(iage=iagemin; iage <= iagemax+3; iage++){ - fprintf(ficresphtm,""); - if(iage==iagemax+1){ - fprintf(ficlog,"1"); - fprintf(ficresphtmfr," "); - }else if(iage==iagemax+2){ - fprintf(ficlog,"0"); - fprintf(ficresphtmfr," "); - }else if(iage==iagemax+3){ - fprintf(ficlog,"Total"); - fprintf(ficresphtmfr," "); - }else{ - if(first==1){ - first=0; - printf("See log file for details...\n"); - } - fprintf(ficresphtmfr," ",iage); - fprintf(ficlog,"Age %d", iage); - } - for(jk=1; jk <=nlstate ; jk++){ - for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++) - pp[jk] += freq[jk][m][iage]; - } - for(jk=1; jk <=nlstate ; jk++){ - for(m=-1, pos=0; m <=0 ; m++) - pos += freq[jk][m][iage]; - if(pp[jk]>=1.e-10){ - if(first==1){ - printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]); - } - fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]); - }else{ - if(first==1) - printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk); - fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk); - } - } - - for(jk=1; jk <=nlstate ; jk++){ - /* posprop[jk]=0; */ - for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */ - pp[jk] += freq[jk][m][iage]; - } /* pp[jk] is the total number of transitions starting from state jk and any ending status until this age */ - - for(jk=1,pos=0, pospropta=0.; jk <=nlstate ; jk++){ - pos += pp[jk]; /* pos is the total number of transitions until this age */ - posprop[jk] += prop[jk][iage]; /* prop is the number of transitions from a live state - from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */ - pospropta += prop[jk][iage]; /* prop is the number of transitions from a live state - from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */ - } - for(jk=1; jk <=nlstate ; jk++){ - if(pos>=1.e-5){ - if(first==1) - printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos); - fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos); - }else{ - if(first==1) - printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk); - fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk); - } - if( iage <= iagemax){ - if(pos>=1.e-5){ - fprintf(ficresp," %d %.5f %.0f %.0f",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta); - fprintf(ficresphtm,"",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta); - /*probs[iage][jk][j1]= pp[jk]/pos;*/ - /*printf("\niage=%d jk=%d j1=%d %.5f %.0f %.0f %f",iage,jk,j1,pp[jk]/pos, pp[jk],pos,probs[iage][jk][j1]);*/ - } - else{ - fprintf(ficresp," %d NaNq %.0f %.0f",iage,prop[jk][iage],pospropta); - fprintf(ficresphtm,"",iage, prop[jk][iage],pospropta); - } - } - pospropt[jk] +=posprop[jk]; - } /* end loop jk */ - /* pospropt=0.; */ - for(jk=-1; jk <=nlstate+ndeath; jk++){ - for(m=-1; m <=nlstate+ndeath; m++){ - if(freq[jk][m][iage] !=0 ) { /* minimizing output */ - if(first==1){ - printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]); - } - fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iage]); - } - if(jk!=0 && m!=0) - fprintf(ficresphtmfr," ",freq[jk][m][iage]); - } - } /* end loop jk */ - posproptt=0.; - for(jk=1; jk <=nlstate; jk++){ - posproptt += pospropt[jk]; - } - fprintf(ficresphtmfr,"\n "); - if(iage <= iagemax){ - fprintf(ficresp,"\n"); - fprintf(ficresphtm,"\n"); - } - if(first==1) - printf("Others in log...\n"); - fprintf(ficlog,"\n"); - } /* end loop age iage */ - fprintf(ficresphtm,""); - for(jk=1; jk <=nlstate ; jk++){ - if(posproptt < 1.e-5){ - fprintf(ficresphtm,"",pospropt[jk],posproptt); - }else{ - fprintf(ficresphtm,"",pospropt[jk]/posproptt,pospropt[jk],posproptt); - } - } - fprintf(ficresphtm,"\n"); - fprintf(ficresphtm,"
Age%d%d
0
Unknown
Total
%d%d%.5f%.0f%.0f%dNaNq%.0f%.0f%.0f
TotNanq%.0f%.0f%.5f%.0f%.0f
\n"); - fprintf(ficresphtmfr,"\n"); - if(posproptt < 1.e-5){ - fprintf(ficresphtm,"\n

This combination (%d) is not valid and no result will be produced

",j1); - fprintf(ficresphtmfr,"\n

This combination (%d) is not valid and no result will be produced

",j1); - fprintf(ficres,"\n This combination (%d) is not valid and no result will be produced\n\n",j1); - invalidvarcomb[j1]=1; - }else{ - fprintf(ficresphtm,"\n

This combination (%d) is valid and result will be produced.

",j1); - invalidvarcomb[j1]=0; - } - fprintf(ficresphtmfr,"\n"); - } /* end selected combination of covariate j1 */ - dateintmean=dateintsum/k2cpt; + dateintsum=0; + k2cpt=0; + /* For that comination of covariate j1, we count and print the frequencies */ + for (iind=1; iind<=imx; iind++) { /* For each individual iind */ + bool=1; + if (nqfveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */ + for (z1=1; z1<= nqfveff; z1++) { + meanq[z1]+=coqvar[Tvar[z1]][iind]; + } + for (z1=1; z1<=ncoveff; z1++) { + /* if(Tvaraff[z1] ==-20){ */ + /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */ + /* }else if(Tvaraff[z1] ==-10){ */ + /* /\* sumnew+=coqvar[z1][iind]; *\/ */ + /* }else */ + if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ + /* Tests if this individual i responded to j1 (V4=1 V3=0) */ + bool=0; + /* printf("bool=%d i=%d, z1=%d, Tvaraff[%d]=%d, covar[Tvarff][%d]=%2f, codtabm(%d,%d)=%d, nbcode[Tvaraff][codtabm(%d,%d)=%d, j1=%d\n", + bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1), + j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/ + /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/ + } + } /* end z1 */ + } /* cptcovn > 0 */ + + if (bool==1){ /* We selected an individual iin satisfying combination j1 */ + /* for(m=firstpass; m<=lastpass; m++){ */ + for(mi=1; mi=firstpass && m <=lastpass){ + k2=anint[m][iind]+(mint[m][iind]/12.); + /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/ + if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */ + if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */ + if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */ + prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */ + if (m1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99)) { + dateintsum=dateintsum+k2; + k2cpt++; + /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */ + } + /*}*/ + } /* end m */ + } /* end bool */ + } /* end iind = 1 to imx */ + /* prop[s][age] is feeded 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 */ + + + /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/ + pstamp(ficresp); + if (ncoveff>0) { + fprintf(ficresp, "\n#********** Variable "); + fprintf(ficresphtm, "\n

********** Variable "); + fprintf(ficresphtmfr, "\n

********** Variable "); + for (z1=1; z1<=ncoveff; z1++){ + fprintf(ficresp, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresphtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresphtmfr, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + } + fprintf(ficresp, "**********\n#"); + fprintf(ficresphtm, "**********

\n"); + fprintf(ficresphtmfr, "**********\n"); + fprintf(ficlog, "\n#********** Variable "); + for (z1=1; z1<=ncoveff; z1++) fprintf(ficlog, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficlog, "**********\n"); + } + fprintf(ficresphtm,""); + for(i=1; i<=nlstate;i++) { + fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i); + fprintf(ficresphtm, "",i,i); + } + fprintf(ficresp, "\n"); + fprintf(ficresphtm, "\n"); + + /* Header of frequency table by age */ + fprintf(ficresphtmfr,"
AgePrev(%d)N(%d)N
"); + fprintf(ficresphtmfr," "); + for(jk=-1; jk <=nlstate+ndeath; jk++){ + for(m=-1; m <=nlstate+ndeath; m++){ + if(jk!=0 && m!=0) + fprintf(ficresphtmfr," ",jk,m); + } + } + fprintf(ficresphtmfr, "\n"); + + /* For each age */ + for(iage=iagemin; iage <= iagemax+3; iage++){ + fprintf(ficresphtm,""); + if(iage==iagemax+1){ + fprintf(ficlog,"1"); + fprintf(ficresphtmfr," "); + }else if(iage==iagemax+2){ + fprintf(ficlog,"0"); + fprintf(ficresphtmfr," "); + }else if(iage==iagemax+3){ + fprintf(ficlog,"Total"); + fprintf(ficresphtmfr," "); + }else{ + if(first==1){ + first=0; + printf("See log file for details...\n"); + } + fprintf(ficresphtmfr," ",iage); + fprintf(ficlog,"Age %d", iage); + } + for(jk=1; jk <=nlstate ; jk++){ + for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++) + pp[jk] += freq[jk][m][iage]; + } + for(jk=1; jk <=nlstate ; jk++){ + for(m=-1, pos=0; m <=0 ; m++) + pos += freq[jk][m][iage]; + if(pp[jk]>=1.e-10){ + if(first==1){ + printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]); + } + fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]); + }else{ + if(first==1) + printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk); + fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk); + } + } + + for(jk=1; jk <=nlstate ; jk++){ + /* posprop[jk]=0; */ + for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */ + pp[jk] += freq[jk][m][iage]; + } /* pp[jk] is the total number of transitions starting from state jk and any ending status until this age */ + + for(jk=1,pos=0, pospropta=0.; jk <=nlstate ; jk++){ + pos += pp[jk]; /* pos is the total number of transitions until this age */ + posprop[jk] += prop[jk][iage]; /* prop is the number of transitions from a live state + from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */ + pospropta += prop[jk][iage]; /* prop is the number of transitions from a live state + from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */ + } + for(jk=1; jk <=nlstate ; jk++){ + if(pos>=1.e-5){ + if(first==1) + printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos); + fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos); + }else{ + if(first==1) + printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk); + fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk); + } + if( iage <= iagemax){ + if(pos>=1.e-5){ + fprintf(ficresp," %d %.5f %.0f %.0f",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta); + fprintf(ficresphtm,"",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta); + /*probs[iage][jk][j1]= pp[jk]/pos;*/ + /*printf("\niage=%d jk=%d j1=%d %.5f %.0f %.0f %f",iage,jk,j1,pp[jk]/pos, pp[jk],pos,probs[iage][jk][j1]);*/ + } + else{ + fprintf(ficresp," %d NaNq %.0f %.0f",iage,prop[jk][iage],pospropta); + fprintf(ficresphtm,"",iage, prop[jk][iage],pospropta); + } + } + pospropt[jk] +=posprop[jk]; + } /* end loop jk */ + /* pospropt=0.; */ + for(jk=-1; jk <=nlstate+ndeath; jk++){ + for(m=-1; m <=nlstate+ndeath; m++){ + if(freq[jk][m][iage] !=0 ) { /* minimizing output */ + if(first==1){ + printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]); + } + fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iage]); + } + if(jk!=0 && m!=0) + fprintf(ficresphtmfr," ",freq[jk][m][iage]); + } + } /* end loop jk */ + posproptt=0.; + for(jk=1; jk <=nlstate; jk++){ + posproptt += pospropt[jk]; + } + fprintf(ficresphtmfr,"\n "); + if(iage <= iagemax){ + fprintf(ficresp,"\n"); + fprintf(ficresphtm,"\n"); + } + if(first==1) + printf("Others in log...\n"); + fprintf(ficlog,"\n"); + } /* end loop age iage */ + fprintf(ficresphtm,""); + for(jk=1; jk <=nlstate ; jk++){ + if(posproptt < 1.e-5){ + fprintf(ficresphtm,"",pospropt[jk],posproptt); + }else{ + fprintf(ficresphtm,"",pospropt[jk]/posproptt,pospropt[jk],posproptt); + } + } + fprintf(ficresphtm,"\n"); + fprintf(ficresphtm,"
Age%d%d
0
Unknown
Total
%d%d%.5f%.0f%.0f%dNaNq%.0f%.0f%.0f
TotNanq%.0f%.0f%.5f%.0f%.0f
\n"); + fprintf(ficresphtmfr,"\n"); + if(posproptt < 1.e-5){ + fprintf(ficresphtm,"\n

This combination (%d) is not valid and no result will be produced

",j1); + fprintf(ficresphtmfr,"\n

This combination (%d) is not valid and no result will be produced

",j1); + fprintf(ficres,"\n This combination (%d) is not valid and no result will be produced\n\n",j1); + invalidvarcomb[j1]=1; + }else{ + fprintf(ficresphtm,"\n

This combination (%d) is valid and result will be produced.

",j1); + invalidvarcomb[j1]=0; + } + fprintf(ficresphtmfr,"\n"); + } /* end selected combination of covariate j1 */ + dateintmean=dateintsum/k2cpt; - fclose(ficresp); - fclose(ficresphtm); - fclose(ficresphtmfr); - free_vector(meanq,1,nqfveff); - free_matrix(meanqt,1,lastpass,1,nqtveff); - free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+3+AGEMARGE); - free_vector(pospropt,1,nlstate); - free_vector(posprop,1,nlstate); - free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+3+AGEMARGE); - free_vector(pp,1,nlstate); - /* End of freqsummary */ - } + fclose(ficresp); + fclose(ficresphtm); + fclose(ficresphtmfr); + free_vector(meanq,1,nqfveff); + free_matrix(meanqt,1,lastpass,1,nqtveff); + free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+3+AGEMARGE); + free_vector(pospropt,1,nlstate); + free_vector(posprop,1,nlstate); + free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+3+AGEMARGE); + free_vector(pp,1,nlstate); + /* End of freqsummary */ +} /************ Prevalence ********************/ void prevalence(double ***probs, double agemin, double agemax, int **s, double **agev, int nlstate, int imx, int *Tvar, int **nbcode, int *ncodemax,double **mint,double **anint, double dateprev1,double dateprev2, int firstpass, int lastpass) @@ -7590,6 +7613,7 @@ int readdata(char datafile[], int firsto return 1; } coqvar[iv][i]=dval; + covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */ } strcpy(line,stra); }/* end loop nqv */ @@ -7798,7 +7822,7 @@ int decodemodel ( char model[], int last 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 */ - Typevar[k]=1; /* 2 for age product */ + 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 */ /*printf("stre=%s ", stre);*/ @@ -7863,28 +7887,112 @@ int decodemodel ( char model[], int last /* Decodemodel knows only the grammar (simple, product, age*) of the model but not what kind of variable (dummy vs quantitative, fixed vs time varying) is behind */ -/* ncovcol= 1, nqv=1, ntv=2, nqtv= 1 = 5 possible variables data - model= V2 + V4 +V3 + V4*V3 + V5*age + V5 , V1 is not used saving its place - k = 1 2 3 4 5 6 - Tvar[k]= 2 4 3 1+1+2+1+1=6 5 5 - Typevar[k]=0 0 0 2 1 0 +/* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying + 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 + Fixed[Tvar[k]]1 1 1 1 2 0 1 2 3 + Dummy[Tvar[k]]1 0 0 0 2 1 1 2 3 */ /* Dispatching between quantitative and time varying covariates */ + /* 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 */ for(k=1, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0;k<=cptcovt; k++){ /* or cptocvt */ - if (Tvar[k] <=ncovcol){ /* Simple fixed dummy covariatee */ + if (Tvar[k] <=ncovcol && (Typevar[k]==0 || Typevar[k]==2)){ /* Simple or product fixed dummy covariatee */ + Fixed[Tvar[k]]= 0; + Dummy[Tvar[k]]= 0; ncoveff++; }else if( Tvar[k] <=ncovcol+nqv && Typevar[k]==0){ /* Remind that product Vn*Vm are added in k*/ + Fixed[Tvar[k]]= 0; + Dummy[Tvar[k]]= 1; nqfveff++; /* Only simple fixed quantitative variable */ }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 0; ntveff++; /* Only simple time varying dummy variable */ - }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ - nqtveff++;/* Only simple time varying quantitative variable */ + }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){ + if( Typevar[k]==0){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + nqtveff++;/* Only simple time varying quantitative variable */ + } + }else if (Typevar[k] == 2) { + for(k1=1; k1 <= cptcovprodnoage; k1++){ + if(Tvard[k1][1] <=ncovcol){ + if(Tvard[k1][2] <=ncovcol){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 0; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[Tvar[k]]= 0; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 0; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + } + }else if(Tvard[k1][1] <=ncovcol+nqv){ + if(Tvard[k1][2] <=ncovcol){ + Fixed[Tvar[k]]= 0; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[Tvar[k]]= 0; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + } + }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ + if(Tvard[k1][2] <=ncovcol){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 0; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + } + }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ + if(Tvard[k1][2] <=ncovcol){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[Tvar[k]]= 1; + Dummy[Tvar[k]]= 1; + } + }else{ + printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]); + fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]); + } + } /* end k1 */ }else{ - printf("Other types in effective covariates \n"); + printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]); + fprintf(ficlog,"Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]); } + printf("Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[Tvar[k]],Dummy[Tvar[k]]); + fprintf(ficlog,"Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[Tvar[k]],Dummy[Tvar[k]]); } - + printf("Model=%s\n\ +Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\ +Fixed[Tvar[k]] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product \n\ +Dummy[Tvar[k]] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model); + printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn); fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn); return (0); /* with covar[new additional covariate if product] and Tage if age */ @@ -9036,28 +9144,28 @@ run imach with mle=-1 to get a correct t /* Scans npar lines */ for(i=1; i <=npar; i++){ - count=fscanf(ficpar,"%1d%1d%1d",&i1,&j1,&jk); + count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk); if(count != 3){ - printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\ + printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\ This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\ Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model); - fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\ + fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\ This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\ Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model); - exit(1); + exit(1); }else{ - if(mle==1) - printf("%1d%1d%1d",i1,j1,jk); - } - fprintf(ficlog,"%1d%1d%1d",i1,j1,jk); - fprintf(ficparo,"%1d%1d%1d",i1,j1,jk); + if(mle==1) + printf("%1d%1d%d",i1,j1,jk); + } + fprintf(ficlog,"%1d%1d%d",i1,j1,jk); + fprintf(ficparo,"%1d%1d%d",i1,j1,jk); for(j=1; j <=i; j++){ - fscanf(ficpar," %le",&matcov[i][j]); - if(mle==1){ - printf(" %.5le",matcov[i][j]); - } - fprintf(ficlog," %.5le",matcov[i][j]); - fprintf(ficparo," %.5le",matcov[i][j]); + fscanf(ficpar," %le",&matcov[i][j]); + if(mle==1){ + printf(" %.5le",matcov[i][j]); + } + fprintf(ficlog," %.5le",matcov[i][j]); + fprintf(ficparo," %.5le",matcov[i][j]); } fscanf(ficpar,"\n"); numlinepar++; @@ -9069,7 +9177,7 @@ Please run with mle=-1 to get a correct /* End of read covariance matrix npar lines */ for(i=1; i <=npar; i++) for(j=i+1;j<=npar;j++) - matcov[i][j]=matcov[j][i]; + matcov[i][j]=matcov[j][i]; if(mle==1) printf("\n"); @@ -9129,7 +9237,9 @@ Please run with mle=-1 to get a correct k=1 Tvar[1]=2 (from V2) */ Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */ - Typevar=ivector(1,NCOVMAX); /* -1 to 4 */ + Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */ + Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */ + Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */ /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs). For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4, Tvar[4=age*V3] is 3 and 'age' is recorded in Tage. @@ -9416,33 +9526,33 @@ Interval (in months) between two waves: for (i=1; i<=imx; i++){ dcwave[i]=-1; for (m=firstpass; m<=lastpass; m++) - if (s[m][i]>nlstate) { - dcwave[i]=m; - /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/ - break; - } + if (s[m][i]>nlstate) { + dcwave[i]=m; + /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/ + break; + } } - + for (i=1; i<=imx; i++) { if (wav[i]>0){ - ageexmed[i]=agev[mw[1][i]][i]; - j=wav[i]; - agecens[i]=1.; - - if (ageexmed[i]> 1 && wav[i] > 0){ - agecens[i]=agev[mw[j][i]][i]; - cens[i]= 1; - }else if (ageexmed[i]< 1) - cens[i]= -1; - if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass) - cens[i]=0 ; + ageexmed[i]=agev[mw[1][i]][i]; + j=wav[i]; + agecens[i]=1.; + + if (ageexmed[i]> 1 && wav[i] > 0){ + agecens[i]=agev[mw[j][i]][i]; + cens[i]= 1; + }else if (ageexmed[i]< 1) + cens[i]= -1; + if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass) + cens[i]=0 ; } else cens[i]=-1; } for (i=1;i<=NDIM;i++) { for (j=1;j<=NDIM;j++) - ximort[i][j]=(i == j ? 1.0 : 0.0); + ximort[i][j]=(i == j ? 1.0 : 0.0); } /*p[1]=0.0268; p[NDIM]=0.083;*/ @@ -10275,6 +10385,8 @@ Please run with mle=-1 to get a correct free_ivector(ncodemax,1,NCOVMAX); free_ivector(ncodemaxwundef,1,NCOVMAX); + free_ivector(Dummy,-1,NCOVMAX); + free_ivector(Fixed,-1,NCOVMAX); free_ivector(Typevar,-1,NCOVMAX); free_ivector(Tvar,1,NCOVMAX); free_ivector(Tprod,1,NCOVMAX);