I'm having some problems with to categorize the characteristics of each variable using quartiles. Using the code below. ods trace on; /* Calculate Means and Standard Deviations */ PROC MEANS DATA=CoAnl.Combined_analysis MEAN STDDEV; CLASS Quartiles; VAR avg_Risk_Physical_Activity avg_dem_pctn4 Dem_Poverty_PC_Income avg_Out_Depres_Disor_CT; OUTPUT OUT=Means_StdDevs MEAN=Mean_ STDDEV=StdDev_; RUN; /* Perform ANOVA with LSMEANS for p-values */ PROC GLM DATA=CoAnl.Combined_analysis; CLASS Quartiles; MODEL avg_Risk_Physical_Activity avg_dem_pctn4 Dem_Poverty_PC_Income avg_Out_Depres_Disor_CT = Quartiles; LSMEANS Quartiles / adjust=tukey; RUN; ods trace off; ods output OverallANOVA=table22; PROC GLM DATA=CoAnl.Combined_analysis; CLASS Quartiles; MODEL avg_Risk_Physical_Activity avg_dem_pctn4 Dem_Poverty_PC_Income avg_Out_Depres_Disor_CT = Quartiles; LSMEANS Quartiles / adjust=tukey; RUN; proc sql; create table FINAL2 as select a.Variable,a.MeanSD, b.Probf label='p-Value' from table_Mean a left join table22(where =(source="Model"))b on a.variable =b.dependent; quit; Proc print data=FINAL2; run; Result Obs Variable MeanSD ProbF12 4 Income 14.9(8.6) 0.1919 Depressive Disorder 17.3(5.4) <.0001 physical activity 19.7(8.5) 0.2182 Bachelors Degree or Higher 33.9(14.7) 0.4753 I tried to put the quartiles level in the Final table above when I used the proc print to make it seem like the image below, butI didn't know the appropriate code for that. Result Depression Quartiles N Obs Variable Mean Std Dev0 21 avg_Risk_Physical_Activity avg_dem_pctn4 Dem_Poverty_PC_Income avg_Out_Depres_Disor_CT 1 11 avg_Risk_Physical_Activity avg_dem_pctn4 Dem_Poverty_PC_Income avg_Out_Depres_Disor_CT 2 3 avg_Risk_Physical_Activity avg_dem_pctn4 Dem_Poverty_PC_Income avg_Out_Depres_Disor_CT 3 29 avg_Risk_Physical_Activity avg_dem_pctn4 Dem_Poverty_PC_Income avg_Out_Depres_Disor_CT 22.1945351 30.2583750 17.3667744 12.2072732 11.9459745 12.1870208 11.2971989 2.8700233 21.3504732 32.1421576 16.2652755 16.6428227 6.4469325 22.3623002 8.7059777 0.8111580 19.4700000 35.8216667 17.3083333 17.9250000 6.9890414 18.1325786 8.6883663 1.0158125 17.3202876 36.7880271 12.3661449 21.2076199 5.6867116 12.5118479 5.5296109 4.8850090 Your help is really appreciated.
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