Hi,    I performed a confirmatory factor analysis with proc calis (see code below). I also want to report the '% of the explained variance' for this model (as this was also reported in the same way by other papers).  How can I calculate this explained variance?  Many thanks!        ods graphics on; proc calis data = final plots=pathdiagram outstat  = test ;   factor  freq_social_role ==> D1a_s, freq_social_role ==> D2a_s, freq_social_role ==> D3a_s, freq_social_role ==> D5a_s, freq_social_role ==> D6a_s, freq_social_role ==> D9a_s, freq_social_role ==> D11a_s, freq_social_role ==> D12a_s, freq_social_role ==> D14a_s,   freq_personal_role ==> D4a_s, freq_personal_role ==> D7a_s, freq_personal_role ==> D8a_s, freq_personal_role ==> D10a_s, freq_personal_role ==> D13a_s, freq_personal_role ==> D15a_s, freq_personal_role ==> D16a_s; pvar  freq_social_role = 1.,  freq_personal_role = 1.; fitindex  noindextype on(only)=[chisq df probchi rmsea  srmr bentlercfi]; run;  ods graphics off;   ... View more

Hi,    I have a question regarding non-parametric analyses on multiple imputated datasets.  I performed the imputation with proc mi, and now I want to use proc npar1way as the data is not normally distributed.    I used the following statement with proc GLM + proc mianalyze as parametric way to compare three groups ; now I want to try this in a non-parametric way (comparing three groups). Is this even possible on an imputed dataset?    thank you for your help!  *statement after proc mi - parametric* proc rank data = test out = rank_walk3 groups = 3; var walk_3M; ranks walk_ranks_MI; run; proc sort ; by _Imputation_; run;   proc glm data=rank_walk3; ods select ParameterEstimates; ods select lsmeans; by _Imputation_; class walk_ranks_MI (ref = '0'); model delta = walk_ranks_MI dam_baseline/solution; lsmeans walk_ranks_MI / stderr pdiff cl; ods output ParameterEstimates=glmparms; ods output lsmeans = lsmeans_ds; run; data glmparms_; set glmparms; if parameter='walk_ranks_MI 0' then parameter='rank0'; if parameter='walk_ranks_MI 1' then parameter='rank1'; if parameter='walk_ranks_MI 2' then parameter='rank2'; run;   proc mianalyze parms=glmparms_; modeleffects Intercept rank1 rank2 DAM_baseline ; ods select ParameterEstimates; run;   ... View more