--- imach/src/imach.c 2022/08/25 09:08:41 1.334 +++ imach/src/imach.c 2022/08/31 09:52:36 1.336 @@ -1,6 +1,12 @@ -/* $Id: imach.c,v 1.334 2022/08/25 09:08:41 brouard Exp $ +/* $Id: imach.c,v 1.336 2022/08/31 09:52:36 brouard Exp $ $State: Exp $ $Log: imach.c,v $ + Revision 1.336 2022/08/31 09:52:36 brouard + *** empty log message *** + + Revision 1.335 2022/08/31 08:23:16 brouard + Summary: improvements... + Revision 1.334 2022/08/25 09:08:41 brouard Summary: In progress for quantitative @@ -1281,25 +1287,25 @@ typedef struct { #define ODIRSEPARATOR '\\' #endif -/* $Id: imach.c,v 1.334 2022/08/25 09:08:41 brouard Exp $ */ +/* $Id: imach.c,v 1.336 2022/08/31 09:52:36 brouard Exp $ */ /* $State: Exp $ */ #include "version.h" char version[]=__IMACH_VERSION__; char copyright[]="August 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: 1.334 $ $Date: 2022/08/25 09:08:41 $"; +char fullversion[]="$Revision: 1.336 $ $Date: 2022/08/31 09:52:36 $"; char strstart[80]; char optionfilext[10], optionfilefiname[FILENAMELENGTH]; int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */ int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */ /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */ /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */ -int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age */ +int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age but including products */ int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */ -int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 (dummy or quantit or time varying) */ -int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */ +int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */ +int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */ int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */ int cptcovprodnoage=0; /**< Number of covariate products without age */ -int cptcoveff=0; /* Total number of single dummy covariates to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */ +int cptcoveff=0; /* Total number of single dummy covariates (fixed or time varying) to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */ int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */ int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */ int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */ @@ -3505,7 +3511,8 @@ double **matprod2(double **out, double * double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij, int nres ) { - /* Computes the transition matrix starting at age 'age' and dummies values in each resultline (loop on ij to find the corresponding combination) to over + /* Already optimized with precov. + Computes the transition matrix starting at age 'age' and dummies values in each resultline (loop on ij to find the corresponding combination) to over 'nhstepm*hstepm*stepm' months (i.e. until age (in years) age+nhstepm*hstepm*stepm/12) by multiplying nhstepm*hstepm matrices. @@ -3836,16 +3843,17 @@ double ***hbxij(double ***po, int nhstep /*************** log-likelihood *************/ double func( double *x) { - int i, ii, j, k, mi, d, kk; + int i, ii, j, k, mi, d, kk, kf=0; int ioffset=0; double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1]; double **out; 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, quantitative time varying covariate */ + double bbh, survp; - long ipmx; double agexact; + double agebegin, ageend; /*extern weight */ /* We are differentiating ll according to initial status */ /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/ @@ -3868,12 +3876,12 @@ double func( double *x) */ ioffset=2+nagesqr ; /* Fixed */ - for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */ + for (kf=1; kf<=ncovf;kf++){ /* 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)*/ + cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][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] @@ -3888,7 +3896,8 @@ double func( double *x) But if the variable is not in the model TTvar[iv] is the real variable effective in the model: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i] */ - for(mi=1; mi<= wav[i]-1; mi++){ + for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */ + /* Wave varying (but not age varying) */ 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]; @@ -3898,6 +3907,9 @@ double func( double *x) oldm[ii][j]=(ii==j ? 1.0 : 0.0); savm[ii][j]=(ii==j ? 1.0 : 0.0); } + + agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */ + ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */ 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 */ @@ -4172,7 +4184,7 @@ double func( double *x) double funcone( double *x) { /* Same as func but slower because of a lot of printf and if */ - int i, ii, j, k, mi, d, kk; + int i, ii, j, k, mi, d, kk, kf=0; int ioffset=0; double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1]; double **out; @@ -4195,13 +4207,18 @@ double funcone( double *x) for(k=1; k<=nlstate; k++) ll[k]=0.; ioffset=0; for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + /* Computes the values of the ncovmodel covariates of the model + depending if the covariates are fixed or varying (age dependent) and stores them in cov[] + Then computes with function pmij which return a matrix p[i][j] giving the elementary probability + to be observed in j being in i according to the model. + */ /* ioffset=2+nagesqr+cptcovage; */ ioffset=2+nagesqr; /* 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 *//* 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)*/ + for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */ + cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][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]; */ /* cov[2+6]=covar[2][i]; V2 */ @@ -4212,6 +4229,19 @@ double funcone( double *x) /* cov[2+9]=covar[Tvar[9]][i]; */ /* cov[2+9]=covar[1][i]; V1 */ } + /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4] + 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 + mw[mi][i] is real wave of the mi th effectve wave */ + /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i]; + s2=s[mw[mi+1][i]][i]; + And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i] + But if the variable is not in the model TTvar[iv] is the real variable effective in the model: + meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i] + */ + /* This part may be useless now because everythin should be in covar */ /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */ /* cov[++ioffset]=coqvar[TvarFQ[k]][i];/\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V2 and V1*V2 is fixed (k=6 and 7?)*\/ */ /* } */ @@ -4269,7 +4299,19 @@ double funcone( double *x) savm=oldm; oldm=newm; } /* end mult */ - + /*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]; /* if(s2==-1){ */ @@ -4301,27 +4343,33 @@ double funcone( double *x) 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]); */ + /* printf("Funcone 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],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */ if(globpr){ fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ %11.6f %11.6f %11.6f ", \ num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); + /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */ + /* %11.6f %11.6f %11.6f ", \ */ + /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */ + /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */ for(k=1,llt=0.,l=0.; k<=nlstate; k++){ llt +=ll[k]*gipmx/gsw; fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw); + /* printf(" %10.6f",-ll[k]*gipmx/gsw); */ } fprintf(ficresilk," %10.6f\n", -llt); + /* printf(" %10.6f\n", -llt); */ } - } /* end of wave */ -} /* end of individual */ -for(k=1,l=0.; k<=nlstate; k++) l += ll[k]; + } /* end of wave */ + } /* end of individual */ + for(k=1,l=0.; k<=nlstate; k++) l += ll[k]; /* printf("l1=%f l2=%f ",ll[1],ll[2]); */ -l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */ -if(globpr==0){ /* First time we count the contributions and weights */ - gipmx=ipmx; - gsw=sw; -} + l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */ + if(globpr==0){ /* First time we count the contributions and weights */ + gipmx=ipmx; + gsw=sw; + } return -l; } @@ -4980,7 +5028,7 @@ Title=%s
Datafile=%s Firstpass=%d La j1=0; /* j=ncoveff; /\* Only fixed dummy covariates *\/ */ - j=cptcoveff; /* Only dummy covariates used in the model */ + j=cptcoveff; /* Only simple dummy covariates used in the model */ /* j=cptcovn; /\* Only dummy covariates of the model *\/ */ if (cptcovn<1) {j=1;ncodemax[1]=1;} @@ -5001,7 +5049,7 @@ Title=%s
Datafile=%s Firstpass=%d La /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */ /* Loop on nj=1 or 2 if dummy covariates j!=0 - * Loop on j1(1 to 2**cptcovn) covariate combination + * Loop on j1(1 to 2**cptcoveff) covariate combination * freq[s1][s2][iage] =0. * Loop on iind * ++freq[s1][s2][iage] weighted @@ -5026,7 +5074,7 @@ Title=%s
Datafile=%s Firstpass=%d La if(nj==1) j=0; /* First pass for the constant */ else{ - j=cptcovs; /* Other passes for the covariate values */ + j=cptcoveff; /* Other passes for the covariate values number of simple covariates in the model V2+V1 =2 (simple dummy fixed or time varying) */ } first=1; for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all dummy covariates combination of the model, ie excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */ @@ -5062,13 +5110,16 @@ Title=%s
Datafile=%s Firstpass=%d La bool=1; if(j !=0){ if(anyvaryingduminmodel==0){ /* If All fixed covariates */ - if (cptcovn >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */ - for (z1=1; z1<=cptcovn; z1++) { /* loops on covariates in the model */ + if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */ + for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */ /* if(Tvaraff[z1] ==-20){ */ /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */ /* }else if(Tvaraff[z1] ==-10){ */ /* /\* sumnew+=coqvar[z1][iind]; *\/ */ /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/ + /* if( iind >=imx-3) printf("Searching error iind=%d Tvaraff[z1]=%d covar[Tvaraff[z1]][iind]=%.f TnsdVar[Tvaraff[z1]]=%d, cptcoveff=%d, cptcovs=%d \n",iind, Tvaraff[z1], covar[Tvaraff[z1]][iind],TnsdVar[Tvaraff[z1]],cptcoveff, cptcovs); */ + if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX) + printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model); if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */ /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */ bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */ @@ -5078,7 +5129,7 @@ Title=%s
Datafile=%s Firstpass=%d La /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/ } /* Onlyf fixed */ } /* end z1 */ - } /* cptcovn > 0 */ + } /* cptcoveff > 0 */ } /* end any */ }/* end j==0 */ if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */ @@ -5087,7 +5138,7 @@ Title=%s
Datafile=%s Firstpass=%d La m=mw[mi][iind]; if(j!=0){ if(anyvaryingduminmodel==1){ /* Some are varying covariates */ - for (z1=1; z1<=cptcovn; z1++) { + for (z1=1; z1<=cptcoveff; z1++) { if( Fixed[Tmodelind[z1]]==1){ iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality. If covariate's @@ -5161,9 +5212,9 @@ Title=%s
Datafile=%s Firstpass=%d La /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/ - if(cptcovn==0 && nj==1) /* no covariate and first pass */ + if(cptcoveff==0 && nj==1) /* no covariate and first pass */ pstamp(ficresp); - if (cptcovn>0 && j!=0){ + if (cptcoveff>0 && j!=0){ pstamp(ficresp); printf( "\n#********** Variable "); fprintf(ficresp, "\n#********** Variable "); @@ -5216,14 +5267,17 @@ Title=%s
Datafile=%s Firstpass=%d La /* } */ fprintf(ficresphtm,""); - if((cptcovn==0 && nj==1)|| nj==2 ) /* no covariate and first pass */ + if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */ fprintf(ficresp, " Age"); - if(nj==2) for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); + if(nj==2) for (z1=1; z1<=cptcoveff; z1++) { + printf(" V%d=%d, z1=%d, Tvaraff[z1]=%d, j1=%d, TnsdVar[Tvaraff[%d]]=%d |",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])], z1, Tvaraff[z1], j1,z1,TnsdVar[Tvaraff[z1]]); + fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); + } for(i=1; i<=nlstate;i++) { - if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i); + if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i); fprintf(ficresphtm, "",i,i); } - if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n"); + if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n"); fprintf(ficresphtm, "\n"); /* Header of frequency table by age */ @@ -5291,14 +5345,14 @@ Title=%s
Datafile=%s Firstpass=%d La } /* Writing ficresp */ - if(cptcovn==0 && nj==1){ /* no covariate and first pass */ + if(cptcoveff==0 && nj==1){ /* no covariate and first pass */ if( iage <= iagemax){ fprintf(ficresp," %d",iage); } }else if( nj==2){ if( iage <= iagemax){ fprintf(ficresp," %d",iage); - for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); + for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); } } for(s1=1; s1 <=nlstate ; s1++){ @@ -5313,7 +5367,7 @@ Title=%s
Datafile=%s Firstpass=%d La } if( iage <= iagemax){ if(pos>=1.e-5){ - if(cptcovn==0 && nj==1){ /* no covariate and first pass */ + if(cptcoveff==0 && nj==1){ /* no covariate and first pass */ fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta); }else if( nj==2){ fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta); @@ -5322,7 +5376,7 @@ Title=%s
Datafile=%s Firstpass=%d La /*probs[iage][s1][j1]= pp[s1]/pos;*/ /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/ } else{ - if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta); + if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta); fprintf(ficresphtm,"",iage, prop[s1][iage],pospropta); } } @@ -5348,7 +5402,7 @@ Title=%s
Datafile=%s Firstpass=%d La } fprintf(ficresphtmfr,"\n "); fprintf(ficresphtm,"\n"); - if((cptcovn==0 && nj==1)|| nj==2 ) { + if((cptcoveff==0 && nj==1)|| nj==2 ) { if(iage <= iagemax) fprintf(ficresp,"\n"); } @@ -5606,7 +5660,7 @@ void prevalence(double ***probs, double if (cptcovn<1) {j=1;ncodemax[1]=1;} first=0; - for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */ + for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */ for (i=1; i<=nlstate; i++) for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++) prop[i][iage]=0.0; @@ -5930,7 +5984,7 @@ void concatwav(int wav[], int **dh, int nbcode[k][j]=0; /* Valgrind */ /* Loop on covariates without age and products and no quantitative variable */ - for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */ + for (k=1; k<=cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */ for (j=-1; (j < maxncov); j++) Ndum[j]=0; if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */ switch(Fixed[k]) { @@ -6030,6 +6084,10 @@ void concatwav(int wav[], int **dh, int } /* end dummy test */ if(Dummy[k]==1 && Typevar[k] !=1){ /* Quantitative 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(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){ + printf("Error k=%d \n",k); + exit(1); + } 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); @@ -6037,7 +6095,7 @@ void concatwav(int wav[], int **dh, int exit(1); } } - } + } /* end Quanti */ } /* 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; @@ -6051,13 +6109,22 @@ void concatwav(int wav[], int **dh, int ij=0; /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */ - for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */ + for (k=1; k<= cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */ + /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */ /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/ /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */ - if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */ + if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */ + /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */ + /* Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product*/ /* If product not in single variable we don't print results */ /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/ - ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */ + ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */ + /* k= 1 2 3 4 5 6 7 8 9 */ + /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */ + /* ij 1 2 3 */ + /* Tvaraff[ij]= 4 3 1 */ + /* Tmodelind[ij]=2 3 9 */ + /* TmodelInvind[ij]=2 1 1 */ Tvaraff[ij]=Tvar[k]; /* For printing combination *//* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, Tvar {5, 4, 3, 6, 5, 2, 7, 1, 1} Tvaraff={4, 3, 1} V4, V3, V1*/ Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */ TmodelInvind[ij]=Tvar[k]- ncovcol-nqv; /* Inverse TmodelInvind[2=V4]=2 second dummy varying cov (V4)4-1-1 {0, 2, 1, } TmodelInvind[3]=1 */ @@ -6073,7 +6140,7 @@ void concatwav(int wav[], int **dh, int } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */ /* ij--; */ /* cptcoveff=ij; /\*Number of total covariates*\/ */ - *cptcov=ij; /* cptcov= Number of total real effective covariates: effective (used as cptcoveff in other functions) + *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions) * because they can be excluded from the model and real * if in the model but excluded because missing values, but how to get k from ij?*/ for(j=ij+1; j<= cptcovt; j++){ @@ -6206,6 +6273,7 @@ void concatwav(int wav[], int **dh, int /* Covariances of health expectancies eij and of total life expectancies according to initial status i, ei. . */ + /* Very time consuming function, but already optimized with precov */ int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji; int nhstepma, nstepma; /* Decreasing with age */ double age, agelim, hf; @@ -10707,9 +10775,17 @@ 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 + 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 */ + /* Please remark that the new variables are model dependent */ + /* If we have 4 variable but the model uses only 3, like in + * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3 + * k= 1 2 3 4 5 6 7 8 + * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing) + * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3 + * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3 + */ 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 */ @@ -11572,7 +11648,7 @@ int back_prevalence_limit(double *p, dou int hPijx(double *p, int bage, int fage){ /*------------- h Pij x at various ages ------------*/ - + /* to be optimized with precov */ int stepsize; int agelim; int hstepm; @@ -11649,7 +11725,7 @@ int hPijx(double *p, int bage, int fage) int hBijx(double *p, int bage, int fage, double ***prevacurrent){ /*------------- h Bij x at various ages ------------*/ - + /* To be optimized with precov */ int stepsize; /* int agelim; */ int ageminl; @@ -12411,7 +12487,7 @@ Please run with mle=-1 to get a correct mint=matrix(1,maxwav,firstobs,lastobs); anint=matrix(1,maxwav,firstobs,lastobs); s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */ - printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); + /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */ tab=ivector(1,NCOVMAX); ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */ ncodemaxwundef=ivector(1,NCOVMAX); /* Number of code per covariate; if - 1 O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */ @@ -12431,6 +12507,7 @@ Please run with mle=-1 to get a correct Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */ TvarsDind=ivector(1,NCOVMAX); /* */ TnsdVar=ivector(1,NCOVMAX); /* */ + /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */ TvarsD=ivector(1,NCOVMAX); /* */ TvarsQind=ivector(1,NCOVMAX); /* */ TvarsQ=ivector(1,NCOVMAX); /* */ @@ -12553,7 +12630,7 @@ Please run with mle=-1 to get a correct Ndum =ivector(-1,NCOVMAX); cptcoveff=0; if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */ - tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */ + tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; as well as calculate cptcoveff or number of total effective dummy covariates*/ } ncovcombmax=pow(2,cptcoveff); @@ -12692,11 +12769,18 @@ Title=%s
Datafile=%s Firstpass=%d La optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); } - fprintf(fichtm,"\n\n\nIMaCh %s\n IMaCh for Interpolated Markov Chain
\nSponsored by Copyright (C) 2002-2015 INED-EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 (Grant-in-Aid for Scientific Research 25293121) - Intel Software 2015-2018
\ -
\n\ + fprintf(fichtm,"\n\n\ +IMaCh %s\n\ + IMaCh for Interpolated Markov Chain
\n\ +Sponsored by Copyright (C) 2002-2015 INED\ +-EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \ +(Grant-in-Aid for Scientific Research 25293121) - \ +Intel Software 2015-2018
\n", optionfilehtm); + + fprintf(fichtm,"
\n\ IMaCh-%s
%s \
\n\ -Title=%s
Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
\n\ +This file: %sTitle=%s
Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
\n\ \n\
\ \n",\ - optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\ + version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \ optionfilefiname,optionfilext,optionfilefiname,optionfilext,\ fileres,fileres,\ filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart); @@ -13019,6 +13103,7 @@ Please run with mle=-1 to get a correct globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */ likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */ printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw); + /* exit(0); */ for (k=1; k<=npar;k++) printf(" %d %8.5f",k,p[k]); printf("\n"); @@ -13716,7 +13801,7 @@ Please run with mle=-1 to get a correct /*---------- State-specific expectancies and variances ------------*/ - + /* Should be moved in a function */ strcpy(filerest,"T_"); strcat(filerest,fileresu); if((ficrest=fopen(filerest,"w"))==NULL) { @@ -13813,7 +13898,7 @@ Please run with mle=-1 to get a correct fprintf(ficlog,"Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */ exit(1); } - } + } /* End loop for each variable in the resultline */ /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */ /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */ /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */ @@ -13840,7 +13925,8 @@ Please run with mle=-1 to get a correct fprintf(ficresvij,"\n#****** "); /* pstamp(ficresvij); */ for(j=1;j<=cptcoveff;j++) - fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); + fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]); + /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */ for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */ fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */ @@ -13874,7 +13960,7 @@ Please run with mle=-1 to get a correct fprintf(ficrest,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally\n in each health state (popbased=1) (mobilav=%d)\n",mobilav); else fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n"); - fprintf(ficrest,"# Age popbased mobilav e.. (std) "); + fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */ for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i); fprintf(ficrest,"\n"); /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */ @@ -13921,12 +14007,12 @@ Please run with mle=-1 to get a correct printf("done selection\n");fflush(stdout); fprintf(ficlog,"done selection\n");fflush(ficlog); - } /* End k selection */ + } /* End k selection or end covariate selection for nres */ printf("done State-specific expectancies\n");fflush(stdout); fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog); - /* variance-covariance of forward period prevalence*/ + /* variance-covariance of forward period prevalence */ varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
AgePrev(%d)N(%d)N%dNaNq%.0f%.0f