Hello:   I have run proc MI with 10 imputations, now I want to combine coefficients and odds ratios to make inferences using MI analyze. The problem I seem to run into is that parameters are not available for the non-selected variables in my var statement (I used the same var statement for imputation, proc logistic and mi analyze). How do I use mi analyze on logistic regression using stepwise selection to choose variables?   Cheers, Michelle   proc logistic data=outfiles.miout; /*logistic regression*/ class AGE_70plus(ref="1") GENDER_male(ref="1") BMI_status(ref="2") ASACLASS_above3(ref="1") FNSTATUS_NotIndependent(ref="1") PMHxSMOKING(ref="1") PMHxALCOHOL(ref="1") PMHxCAD(ref="1") PMHxCHF(ref="1") PMHxDIABETES(ref="1") PMHxHTN(ref="1") PMHxSTEROIDS(ref="1") PMHxCOPD(ref="1") PMHxDYSPNEA(ref="1") PMHxTIACVA(ref="1") PMHxNEUROIMP(ref="1") PMHxBLEEDINGDISORDER(ref="1") PMHxRENALFAIL PMHxPVD(ref="1") PMHxCANCER(ref="1"); model COMPLICATIONS (descending)= AGE_40plus AGE_50plus AGE_60plus AGE_70plus AGE_80plus GENDER_male BMI_status ASACLASS_above3 FNSTATUS_NotIndependent PMHxSMOKING PMHxALCOHOL PMHxCAD PMHxCHF PMHxDIABETES PMHxHTN PMHxSTEROIDS PMHxCOPD PMHxDYSPNEA PMHxTIACVA PMHxNEUROIMP PMHxBLEEDINGDISORDER PMHxRENALFAIL PMHxPVD PMHxCANCER / selection=stepwise slentry=0.10 slstay=0.05 details lackfit; by _imputation_; ods output ParameterEstimates=outfiles.lgsparms OddsRatios=outfiles.lgsodds; run; proc mianalyze parms(classvar=classval)=outfiles.lgsparms; /*pooling coefficients*/ class AGE_70plus GENDER_male BMI_status ASACLASS_above3 FNSTATUS_NotIndependent PMHxSMOKING PMHxALCOHOL PMHxCAD PMHxCHF PMHxDIABETES PMHxHTN PMHxSTEROIDS PMHxCOPD PMHxDYSPNEA PMHxTIACVA PMHxNEUROIMP PMHxBLEEDINGDISORDER PMHxRENALFAIL PMHxPVD PMHxCANCER; modeleffects AGE_70plus GENDER_male BMI_status ASACLASS_above3 FNSTATUS_NotIndependent PMHxSMOKING PMHxALCOHOL PMHxCAD PMHxCHF PMHxDIABETES PMHxHTN PMHxSTEROIDS PMHxCOPD PMHxDYSPNEA PMHxTIACVA PMHxNEUROIMP PMHxBLEEDINGDISORDER PMHxRENALFAIL PMHxPVD PMHxCANCER; ods output parameterestimates=outfiles.mianalyze_parms CovB=outfiles.mianalyze_covb; run;   ... View more

I have my model parameters from proc logistic pooled using mianalyze. Now, I want to use that model to (2) get the ROC curve for the training set, and (2) make predictions on a validation set. How would I go about doing this. My model is stored as parameter estimates.   proc logistic data=outfiles.daysurg07_16_miout; /*logistic regression*/ class AGE_18to30 AGE_31to40 AGE_51to60 AGE_41to50 AGE_61to70 AGE_71to80 AGE_81plus GENDER_male BMI_obese BMI_overweight BMI_normal BMI_underweight ASACLASS_above3 FNSTATUS_NotIndependent PMHxSMOKING PMHxALCOHOL PMHxCAD PMHxCHF PMHxDIABETES PMHxHTN PMHxSTEROIDS PMHxCOPD PMHxDYSPNEA PMHxTIACVA PMHxNEUROIMP PMHxBLEEDINGDISORDER PMHxRENALFAIL PMHxPVD PMHxCANCER PREGNANT SURG_TYPE; model COMPLICATIONS (descending)= AGE_18to30 AGE_31to40 AGE_51to60 AGE_41to50 AGE_61to70 AGE_71to80 AGE_81plus GENDER_male BMI_obese BMI_overweight BMI_normal BMI_underweight ASACLASS_above3 FNSTATUS_NotIndependent PMHxSMOKING PMHxALCOHOL PMHxCAD PMHxCHF PMHxDIABETES PMHxHTN PMHxSTEROIDS PMHxCOPD PMHxDYSPNEA PMHxTIACVA PMHxNEUROIMP PMHxBLEEDINGDISORDER PMHxRENALFAIL PMHxPVD PMHxCANCER PREGNANT SURG_TYPE / selection=stepwise slentry=0.10 slstay=0.15 details lackfit; by _imputation_; ods output ParameterEstimates=outfiles.lgsparms OddsRatio=outfiles.lgsodds; proc mianalyze parms(classvar=classval)=outfiles.lgsparms; /*pooling coefficients*/ class AGE_18to30 AGE_31to40 AGE_51to60 AGE_41to50 AGE_61to70 AGE_71to80 AGE_81plus GENDER_male BMI_obese BMI_overweight BMI_normal BMI_underweight ASACLASS_above3 FNSTATUS_NotIndependent PMHxSMOKING PMHxALCOHOL PMHxCAD PMHxCHF PMHxDIABETES PMHxHTN PMHxSTEROIDS PMHxCOPD PMHxDYSPNEA PMHxTIACVA PMHxNEUROIMP PMHxBLEEDINGDISORDER PMHxRENALFAIL PMHxPVD PMHxCANCER PREGNANT SURG_TYPE; modeleffects AGE_18to30 AGE_31to40 AGE_51to60 AGE_41to50 AGE_61to70 AGE_71to80 AGE_81plus GENDER_male BMI_obese BMI_overweight BMI_normal BMI_underweight ASACLASS_above3 FNSTATUS_NotIndependent PMHxSMOKING PMHxALCOHOL PMHxCAD PMHxCHF PMHxDIABETES PMHxHTN PMHxSTEROIDS PMHxCOPD PMHxDYSPNEA PMHxTIACVA PMHxNEUROIMP PMHxBLEEDINGDISORDER PMHxRENALFAIL PMHxPVD PMHxCANCER PREGNANT SURG_TYPE; ods output parameterestimates=outfiles.mianalyze_parms_f CovB=outfiles.mianalyze_covb_f; run; ... View more

How do I do univariate analysis for variable selection, say p<0.1, to enter into the final multivariate model? Do I simply run it one by one per variable, and choose? Or is there a way to loop the variables, or to integrate it into proc logistic (eg, stepwise?)     proc logistic data=outfiles.trial2_miout descending; class AGE_above65 SEX BMI_obese ASACLASS_above4 FNSTATUS2 SMOKE HxDYSPNEA HYPERMED STEROID BLEEDDIS HxDIABETES HxCAD HxNEURO HxCHF HxRENALFAIL HxCOPD HxPVD ASCITES DISCANCR WNDINF TRANSFUS; model majormorbid=AGE_above65 SEX BMI_obese ASACLASS_above4 FNSTATUS2 SMOKE HxDYSPNEA HYPERMED STEROID BLEEDDIS HxDIABETES HxCAD HxNEURO HxCHF HxRENALFAIL HxCOPD HxPVD ASCITES DISCANCR WNDINF TRANSFUS; by _imputation_; ods output ParameterEstimates=outfiles.trial2_logistic_parms; run; proc mianalyze parms=trial2_logistic_parms; class AGE_above65 SEX BMI_obese ASACLASS_above4 FNSTATUS2 SMOKE HxDYSPNEA HYPERMED STEROID BLEEDDIS HxDIABETES HxCAD HxNEURO HxCHF HxRENALFAIL HxCOPD HxPVD ASCITES DISCANCR WNDINF TRANSFUS; modeleffects age_above65 sex bmi_obese asaclass_above4 smoke etoh diabetes_n steroid bleeddis cadhx_n neurohx_n neuro_deficit hxchf acuterenalfail Fnstatus2 HYPERMED DYSPNEA_n HXCOPD ascites discancr pvd_n wndinf_n transfus_n; ods output parameterestimates = trial2_mianalyze_parms; run; data outfiles.trial2_ORs; set trial2_mianalyze_parms; OR=exp(estimate); LCL_OR=exp(LCLMean); UCL_OR=exp(UCLMean); proc print; var OR LCL_OR UCL_OR; run;    ... View more