I used the following code to get a slicefit plot (shown below) through the effectplot statement in Proc PLm   proc sort data=zinc.imputed out=zinc.imputed_srtd; by zns_unic; run; proc surveyreg data=zinc.imputed_srtd; weight nat_weight_bio; cluster psu_no_ov; strata newstrata; class SEX area handwashing p_activity; Format SEX SEX. handwashing $handwashing. p_activity p_act.; effect znspln = spline(zns_unic / naturalcubic basis=tpf(noint) knotmethod=PERCENTILELIST(5 27.5 50 72.5 95)); model N_Mets7 = znspln AGE_in_yr sex handwashing p_activity /solution CLPARM; output out=N_Mets7_Out predicted=Pred lcl=Lower ucl=Upper; store N_Mets7_MODEL; run; proc plm SOURCE = N_Mets7_MODEL; EFFECTPLOT FIT (X=ZNS_UNIC)/ CLM; ODS OUTPUT FITPLOT = zinc.N_Mets7_FIT; RUN; Would you let me know is there any option to change the appearance of the slicefit type of plot through proc SGPLOT? I tried the following code but the curves and straight lines seem weird. I only need two curves with 95% confidence band; one for males and one for females.   PROC SGPLOT DATA=zinc.mean_sbp_FIT NOAUTOLEGEND; BAND UPPER = _UCLM LOWER = _LCLM X=_XCONT1/TRANSPARENCY=.3; SERIES Y = _PREDICTED X=_XCONT1; XAXIS LABEL = "Serum zinc concentration (µg/dL)"; yaxis label = "Predicted systolic blood pressure (mm Hg)"; title "A"; title2 "Fit for mean systolic blood pressure with 95% confidence limits"; run;   ... View more

When I run the following code, I do not get the "parameterestimates" table. Instead, it gives the following warnings: WARNING: Output 'ParameterEstimates' was not created. Make sure that the output object name, label, or path is spelled correctly. Also, verify that the appropriate procedure options are used to produce the requested output object. For example, verify that the NOPRINT option is not used. WARNING: Output 'SplineKnots' was not created. Make sure that the output object name, label, or path is spelled correctly. Also, verify that the appropriate procedure options are used to produce the requested output object. For example, verify that the NOPRINT option is not used. WARNING: Output 'ParameterEstimates' was not created. Make sure that the output object name, label, or path is spelled correctly. Also, verify that the appropriate procedure options are used to produce the requested output object. For example, verify that the NOPRINT option is not used.   Here are my code. Any help please?   proc surveyreg data=zinc.imputed_srtd;; weight nat_weight_bio; cluster psu_no_ov; strata newstrata; class sex area edu_mt p_activity cat_crp; format edu_mt edu. CAT_CRP CRP. AREA AREA.; effect znspln = spline(zns_unic / naturalcubic basis=tpf(noint) knotmethod=PERCENTILELIST(5 27.5 50 72.5 95)); model mean_dbp = znspln age_in_yr sex area edu_mt p_activity cat_crp; OUTPUT OUT=ZINC.RESIDUALS P=P_HAT L=LOWER U=UPPER; ods select ParameterEstimates SplineKnots; ods output ParameterEstimates=zinc.PE; run; ... View more

Here is the code I used to generate the imputed dataset:   proc surveyimpute data=zinc.otms method=hotdeck (selection=weighted) seed=123 ndonors=5; cluster psu_no_ov; strata newstrata; weight nat_weight_bio; cells sex area; class cat_smoke sanitation handwashing drinkingwatersource caste alcohol_y_n edu_pat edu_mat; var cat_smoke sanitation handwashing drinkingwatersource caste alcohol_y_n edu_pat edu_mat N_Mets1 N_Mets2 N_Mets3 N_Mets4 N_Mets5 N_Mets6 N_Mets7 crprt diet p_activity zns_unic sys1 sys2 sys3 dias1 dias2 dias3; output out=zinc.imputed donorid=donor; run; data zinc.imputed; set zinc.imputed; if (ImpIndex = 0) then do; /* Include complete respondents */ do _Imputation_=1 to 5; /* in all imputations. */ output; end; end; else do; /* Put incomplete respondents */ _Imputation_ = ImpIndex; /* in separate imputations. */ output; end; proc sort data=zinc.imputed; by _Imputation_ UnitID; run;   then I ran the following regression using the default varmethod=TSL:   proc surveyreg data=zinc.imputed; by _imputation; cluster psu_no_ov; strata newstrata; weight imp_wt; class cat_zinc; model N_Mets8 = cat_zinc / solution noint; contrast 'contrasting example' cat_zinc -3 -1 1 3; estimate 'overall mean' cat_zinc 0.25 0.25 0.25 0.25; run;   Now, should I combine the results using PROC miANALYZE? OR Should I remove the by _imputation_ statement from the Proc surveyeg step and report the results without using procmianalyze? ... View more

Do I need to use PROC MIANALYZE with complex survey missing data imputed by PROC SURVEYIMPUTE (method = hotdeck, varmethod=none)?     Due to extensive resource-intensiveness (e.g., more than 48 hours to run the proc surveyimpute procedure), I can't use replication-based variance estimation methods because I have seven continuous variables in addition to several class variables. ... View more