Hi, I encounter a problem on Hosmer-Lemeshow goodness-of-fit test getting a warning massage as below. I do not understand the macro running that well, so I copied whole macro here, very long though. I would appreciate very much if you could help me. Thank you in advance.     Error message-----------------------------------------------------------------    ... ... MPRINT(EXP_OBS): *===========================================; MPRINT(EXP_OBS): *Hosmer-Lemeshow goodness-of-fit test ; MPRINT(EXP_OBS): *chi-square=sum{[(Oi-Ei)**2]/[Ei*(1-Ei/Ni)]}; MPRINT(EXP_OBS): *===========================================; MPRINT(EXP_OBS): H_L[ci,]=ndecci*(observci-expectci)*(observci-expectci)/(expectci*(ndecci-expectci)); MPRINT(EXP_OBS): end; WARNING: Division by zero, result set to missing value. operation : / at line 2842 column 1 operands : _TEM1004, _TEM1006 _TEM1004 1 row 1 col (numeric) . _TEM1006 1 row 1 col (numeric) 0 statement : ASSIGN at line 2842 column 1 WARNING: Division by zero, result set to missing value. ... ...   --------------------------------------------------------------------------------     Code-------------------------------------------------------------------------   %MACRO EXP_OBS; *=====================================================; * Expected and observed count and Hosmer Lemeshow Test; *=====================================================; PROC PHREG DATA=&infile outest=betas noprint; %IF %UPCASE(&Model.)=BASIC %THEN %DO; MODEL &Dep_Time*&Dep_Cens(0)=&Basic_XVARS. /RL COVB; %END; %IF %UPCASE(&Model.)=EXT %THEN %DO; MODEL &Dep_Time*&Dep_Cens(0)=&Extend_XVARS. /RL COVB; %END; ID &IDN.; output OUT=observed SURVIVAL=SURVobs xbeta=xbetaobs; RUN; ***Go into IML to compute ; data foriml; set observed ; run; proc means data=foriml n noprint; var xbetaobs; output out=ncount n=n; run; data foriml; set foriml; if _n_=1 then set ncount(keep=n); run; *Now sort by futime*descendingevent; proc sort data=foriml; by &Dep_Time. descending &Dep_Cens; run; proc iml; use foriml; read all var {&idn. xbetaobs &Dep_Time. &Dep_Cens survobs} into dat; close foriml; **Note that survobs is survival probability at observed follow-up time; s0=dat[,5]##exp(-dat[,2]);**Survival probaility at observed follow-up time at zero level of covariates; n = nrow(dat); *number of persons in dataset; cnter = J(n,1,0); do cntJ = 1 to n; cnter[cntJ,] = cntJ; end; dat = dat || cnter; dat2 = dat[,2]; dattmp = dat; dat[rank(dat2),] = dattmp; * Now concatenate a Decile variable ; decile = J(n,1,0); do cnti = 1 to n; do dec = 1 to 10; if round((dec - 1)*(n/10) + 1) <= cnti & cnti <= round(dec*(n/10)) then decile[cnti,] = dec; end; end; dat = dat || decile; * Now re-sort dat as it was; dat6 = dat[,6]; dattmp = dat; dat[rank(dat6),] = dattmp; * Now drop the counter column; dat = dat[,1] || dat[,2] || dat[,3] || dat[,4] || dat[,5] || dat[,7]; dat=dat||s0; alldat=dat[,2:3]||s0; * alldat[,1] = xbetaobs unless replaced by xbetanew, alldat[,2] = &FUTIME; tmp=loc(dat[,4]=1); *location of events; evtdat=alldat[tmp,];*auc at all time points of events; nevt=nrow(evtdat);*number of events; *select max time of event <= &YEAR; xx=0;zz=0; do ii=1 to n; if dat[ii,4]=1 & dat[ii,3] <= &YEAR then do;**events at time <=YEAR; zz=dat[ii,3]; end; if dat[ii,3]>&YEAR. & dat[ii,4]=1 & xx=0 then do; maxfu=zz;*max futime <= &YEAR, since data is sorted by follow-up time; xx=1; end; end; tmpa=evtdat[,2]; obsmaxfu=loc(tmpa=maxfu);*events with max fu <=&YEAR -there could be more than one; ntmp=ncol(obsmaxfu); obsmaxfulast=obsmaxfu[,ntmp];**the coordinate of the last obs, in the given order of evtdat, that is an event with fu <=&YEAR - in case there is more than one such; *compute expected and observed number of events at each person痴 actual follow-up time and prob of event within &YEAR (usually 10*365) by decile of risk; expected=j(10,1,0); observed=expected; probevt=expected; ndec=expected; dec=expected; h_l=expected; do ci=1 to 10; dec[ci,]=ci; expectci= 0;observci=0;probevci=0;ndecci=0; do ei=1 to nevt; do fi=1 to n; if dat[fi,3]>=evtdat[ei,2] & dat[fi,6]=ci then do; if ei>1 then expectci=expectci + 1 - (evtdat[ei,3]/evtdat[ei - 1,3])**(exp(dat[fi,2])); if ei=1 then do; expectci=expectci + 1 - (evtdat[ei,3]/1)**(exp(dat[fi,2])); observci=observci + dat[fi,4]; end; end; if ei=1 then do; if dat[fi,6]=ci then do; probevci=probevci + (1 - evtdat[obsmaxfulast,3]**exp(dat[fi,2])); ndecci=ndecci+1; end; end; end; end; expected[ci,]=expectci; observed[ci,]=observci; ndec[ci,]=ndecci; probevt[ci,]=probevci/ndecci; *===========================================; *Hosmer-Lemeshow goodness-of-fit test ; *chi-square=sum{[(Oi-Ei)**2]/[Ei*(1-Ei/Ni)]}; *===========================================; H_L[ci,]=ndecci*(observci-expectci)*(observci-expectci)/(expectci*(ndecci-expectci)); end; obsexp=dec||ndec||observed||expected||probevt||h_l; obsexnam={"decile" "n" "observed" "expected" "probevt" "h_l"}; create obsexp from obsexp[colname=obsexnam]; append from obsexp; close obsexp; quit; TITLE1 "============================================================="; TITLE2 "*** OBSERVED AND EXPECTED EVENT COUNTs at actual f-U times FOR &Model. MODEL ***"; TITLE3 nd prob of event (probevt) at given time(YEAR)・ TITLE4 "============================================================="; PROC PRINT DATA=obsexp Label NOOBS; var decile n observed expected probevt; sum observed expected; RUN; *===========================================; *Hosmer-Lemeshow goodness-of-fit test ; *chi-square=sum{[(Oi-Ei)**2]/[Ei*(1-Ei/Ni)]}; *===========================================; ods exclude all; PROC MEANS data=obsexp sum; Var H_L; ods output summary=HLTest; RUN; ODS exclude none; Data HLTest; SET HLTest; RENAME H_L_SUM=Chi_Square; p_value=1-probchi(H_L_SUM,8); RUN; TITLE1 "==============================================================="; TITLE2 "*** Hosmer-Lemeshow goodness-of-fit test FOR &Model. MODEL ***"; TITLE3 "==============================================================="; PROC PRINT Data=HLTest noobs; RUN; *=========================================; *Gronnesby and Borgan Tests(Wald) for model; *=========================================; data anal2; set observed; rename xbetaobs=xbeta; run; ODS exclude all; proc univariate data=anal2; var xbeta; output out=dec_xbeta pctlpts=10 to 100 by 10 pctlpre=xbeta; run; data anal2; SET anal2; If _N_=1 then set dec_xbeta; xbeta_dec1=1*(.Z<xbeta<xbeta10); xbeta_dec2=1*(xbeta10<= xbeta <xbeta20); xbeta_dec3=1*(xbeta20<= xbeta <xbeta30); xbeta_dec4=1*(xbeta30<= xbeta <xbeta40); xbeta_dec5=1*(xbeta40<= xbeta <xbeta50); xbeta_dec6=1*(xbeta50<= xbeta <xbeta60); xbeta_dec7=1*(xbeta60<= xbeta <xbeta70); xbeta_dec8=1*(xbeta70<= xbeta <xbeta80); xbeta_dec9=1*(xbeta80<= xbeta <xbeta90); xbeta_dec10=1*(xbeta90<=xbeta); RUN; PROC SORT data=anal2; by &IDN; run; PROC SORT data=&infile; by &IDN; run; %Let xbeta_decs= xbeta_dec2 xbeta_dec3 xbeta_dec4 xbeta_dec5 xbeta_dec6 xbeta_dec7 xbeta_dec8 xbeta_dec9 xbeta_dec10; Data infile_xbeta_dec; merge &infile anal2(Keep=&idn &xbeta_decs); by &idn; run; PROC PHREG DATA=INFILE_xbeta_dec ; %IF %UPCASE(&Model.)=BASIC %THEN %DO; MODEL &Dep_Time*&Dep_Cens(0)=&Basic_XVARS. &xbeta_decs.; %END; %IF %UPCASE(&Model.)=EXT %THEN %DO; MODEL &Dep_Time*&Dep_Cens(0)=&Extend_XVARS. &xbeta_decs.; %END; ID &idn; test1: Test xbeta_dec2, xbeta_dec3, xbeta_dec4, xbeta_dec5, xbeta_dec6, xbeta_dec7, xbeta_dec8, xbeta_dec9, xbeta_dec10; ods output TestStmts=GBChisq; RUN; ODS exclude none; TITLE1 "=============================================================="; TITLE2 "*** Gronnesby and Borgan Tests(Wald) for &Model. Model ***"; TITLE3 "=============================================================="; Proc Format; Value $LableFmt "test1"="GBTest for &Model. Model"; RUN; PROC PRINT data=GBChisq noobs; var Label WaldChisq DF ProbChiSq; Format Label $LableFmt.; RUN; TITLE1 ; TITLE2 ; TITLE3 ; TITLE4 ; TITLE5 ; TITLE6 ; %MEND;   ------------------------------------------------------------------------------------------------ ... View more