

Interpreting effects in Bayes ML path... 

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Hello Drs Muthen! Could you please help me in interpreting one issue related to my results of multilevel path analysis using BAYES estimator? I examined two models: random intercept, random slope models. X,Z and K are level1 predictors A, B, C and D are level2 predictors. Y is the outcome. Random intercept model %WITHIN% Y ON X; Y ON Z; Y ON K; Z ON K; %BETWEEN% Y ON A B C D; A WITH B C D; B WITH C D; C WITH D;  In the above model, K was found to be a significant negative predictor of Z (slope of K = .149, credibility interval [.237,.062]). However, when we allowed for the slopes to vary across groups as in the below model, slope of K was not significant (slope of K = .124, credibility interval [.256,.010] while the variation of the slope across groups was significant ( variance of slope =.059, credibility interval [.014,.158]) . Random slope model %WITHIN% s1  Y ON X; s2  Y ON Z; s3  Y ON K; s4  Z ON k; %BETWEEN% Y ON A B C D; A WITH B C D; B WITH C D; C WITH D; s1 s2 s4 s3;  So, how one can interpret the effect of K on Z in each model? Thanks! 


If your slope variance is substantial, I think you need to go with that model version, that is, the slope mean is not significant. 


Many thanks for your answer! 

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