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08-07-2015 11:42 PM

Dear all,

I am using SAS 9.3 to perform multiple imputation for systolic blood pressure (SBP) through FCS predictive mean matching methods.

We are doing an analysis for a 3-arm randomized clinical study. We measured SBP at baseline and then at 6-month intervals over 2 years. In the analysis, we used Generalized Estimating Equation to analyze baseline and 2 year SBP. The SBP (baseline, 6 m, 12m,18m and 24m) displayed an arbitrary missing pattern(no missing SBP at baseline). Because only baseline and 2 year SBP were analyzed, only 2 year SBP was imputed with FCS predictive mean matching methods. The remaining variables were imputed by SAS default methods.

The variables included in the imputation model for imputing 2 year SBP (sbp_24m) were:

Continuous variables: SBP at baseline, 6 m, 12m,18m (sbp0, sbp_6m ,sbp_12m, sbp_18m ); age, BMI, physical activity score (mets_0)

categorical variables: intervention group (3 categories: treat), gender (binary), education(binary), smoke(binary), diabetes(binary), antihypertensive use(binary: antihyp)

Variables with missing data : sbp_6m sbp_12m sbp_18m sbp_24m, bmi, diabetes.

my codes are:

PROC **mi** data=WORK seed=**20150805** nimpute=**20** out=mi_WORK;

class gender education antihyp smoke diabetes treat ;

var sbp_24m sbp0 sbp_6m sbp_12m sbp_18m age gender education treat bmi smoke METS_0 antihyp Diabetes ;

FCS nbiter=**20** regpmm(sbp_24m=sbp0 sbp_6m sbp_12m sbp_18m age gender education treat bmi smoke METS_0 antihyp Diabetes);

RUN;

The model was run successfully. However, I found that if I changed the order of the variables in the "var" statement (except sbp_24m) or the predictors in regression model of "regpmm" statement, I got different sets of imputed data for SBP_24m. The pooling results from GEE model were thus different each time I changed the order of the variables. In the 'var' statement, sbp_24m is in the first place. I want to impute this variable first and use observed values of other variables to do the imputation. In the "regpmm" state, since this is a regression model, I think the order of the predictors in the model should not affect the imputation results.

Can you tell me why?

Also, should *multicollinearity be considered since I added SBP at different time points into the same model? Finally,*

*will the categorical variables be modeled as categorical variables in the regression model if they are placed in the *

*"class" statement?*

*Thank you very much!*

*LaoLiang*