

Working with pooled data in sem 

Message/Author 


Hi MPLus Team, I have a question concernig the work on pooled data. I want to estimate a MIMICModel with pooled data over different time periods. How is it possible to take the pooling bias into account? Do there excist any option in MPlus which allows a multistep residual analysis? 


I assume that you have several data sets that you want to analyze together that contain different observations but the same variables. You could use multiple group analysis where you test whether these data sets come from the same population. There is no multistep residual analysis in Mplus. 

C. Lechner posted on Wednesday, April 23, 2014  6:23 am



Suppose I am interested in lagged effects of a variable X on a categorical variable Y, moderated by a clusterlevel variable Z. I have pooled longitudinal data from participants who took part in 24 waves. I want to look at lagged effects between pairs of waves (i.e., 12, 23, 34) in a single analysis to maximize power. Can I use the DATA WIDETOLONG command in conjunction with TYPE=COMPLEX TWOLEVEL to take into account both the clustering due to repeated measurement and the clustering due to cluster sampling? My idea was to use WIDETOLONG to create lagged effects by pairing x's measured at time 13 with y's and z's measured at time 24; and to then analyze these data as a multilevel model (threelevel analysis) without the repetitionvariable: DATA WIDETOLONG: WIDE = x1x3  y2y4  z2z4; LONG = x  y  z ; IDVARIABLE = person; REPETITION = time; ... ANALYSIS: TYPE = TWOLEVEL COMPLEX RANDOM; ESTIMATOR = MLR; MODEL: %WITHIN% S  Y ON X; %BETWEEN % Y S ON Z; Y WITH S; This does not seem to account for the fact that the clustervariable Z was measured repeatedly, or does it? Are there any alternatives in Mplus to analyse such data? 

Back to top 

