WAM posted on Wednesday, November 23, 2011 - 12:47 pm
Hello, I tested a reciprocal relationship between two variables (measured at 3 occasions). One of the reviewers insists that the cross-lag model must be tested using M+ by taking the multi-level structure of the data (occasions nested within students, which are nested within classrooms) in to account. Is there such a possibility? Thanks, Wond
Hi, I have a question similar to the one asked by the previous poster. I want to test an autoregressive latent trajectory model incorporating 2 variables measured on 3 occasions. However, the data has a nested structure (students within classrooms). The higher-order units aren't of substantial research interest. I know that multilevel latent growth models and multilevel cross-lagged models can be tested in Mplus, but I haven't seen anything, either in the Mplus documentation or elsewhere, regarding multilevel ALT models. Can this model be specified in Mplus? If so, would TYPE=TWOLEVEL or TYPE=COMPLEX option be more appropriate?
Hello, I am testing a reciprocal and time-lagged relationship between two variables (both variables are time-varying measured at 3 occasions). The data has a multilevel structure such that occasions for both variables are nested in person and person nested in teams. You mentioned to see Example 9.12 but I don't know how to apply that example to my model. It has only one time-varying variables.
The following is how I enterd the model.
VARIABLE: NAMES ARE v001-v246; USEVARIABLES ARE v001 v220 v221 v222 v244 v245 v246 ; Missing are all (999); Cluster is v001;
ANALYSIS: TYPE IS Twolevel Random; ALGORITHM=INTEGRATION;
This looks ok assuming the 2 sets of outcomes are lagged in time. I don't understand why your Between level specification is for only 1 of the 2 processes.
ZHANG Liang posted on Tuesday, August 11, 2015 - 2:12 am
If I'm doing a 2 time กม 2 variable (A and B) cross-lagged analysis, and trying to examine the effect of a BETWEEN level moderator (M) on one of the cross-lagged paths (A1 to B2), is it correct to write the syntax like below?
... VARIABLE: usevar = a1 a2 b1 b2 m; within = a1 b1; between = m; cluster = cls;
MODEL: %WITHIN% s | b2 on a1; b2 on b1; a2 on a1 b1;
%BETWEEN% s b2 on m; ... ------------------ And, is it recommended that to write the last line as "s on m;" instead of "s b2 on m;", when I'm not interested in how the level 2 variable M predict B2?
Q2. That's fine. Just make sure you estimate the variance of b2 on between (and perhaps covariance with s).
Ai Ye posted on Wednesday, August 12, 2015 - 7:00 pm
I tested a bidirectional relationship between two mathematical learning measures (measured at five time points) using a cross-lagged panel model. Correlation analysis reveal a positive relationships between the two measures across time. I used the following codes:
dcas5f with con5f ; dcas4f with con4f ; dcas3f with con3f ; dcas2f with con2f ; dcas1f with con1f ;
dcas5f on dcas4f con4f ; dcas4f on dcas3f con3f ; dcas3f on dcas2f con2f ; dcas2f on dcas1f con1f ;
con5f on con4f dcas4f ; con4f on con3f dcas3f ; con3f on con2f dcas2f ; con2f on con1f dcas1f ;
However, there is one coefficient (con3f predicting dcas4f) that is (unexpectedly) negatively significant. I would like to ask under what circumstance two positively correlated measures could be negatively related in a cross-lagged model and how should I interpret it (as I know that conceptually a higher score in one math measure leads to a higher score in the other math measure)?