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I am interested in comparing groups of people (n = 4) in terms of their patterns of growth over four time points. The focus of this analysis is a hypothesized interaction between time and group. Ordinarily this could be done in a simple repeated measures ANOVA (with a within and between subject factors). But because of missing data, I would like to take advantage of Mplus's capacity to handle missing data. Is there a method in Mplus using either a multiple group or a structural equation format that would accommodate this analysis? Also, would there be a way to conduct post hoc analyses, such as a simple effect of time for each group? (I imagine just examining the significance of the slope parameter by group would permit this.) Thanks very much. |
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I would use multiple-group growth modeling and as you say test for slope mean differences across the groups, e.g. using Wald testing in Model Test. |
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Thank you for the quick and helpful response. Are there syntax examples that could guide my analysis? I have searched the website and not found any that are specifically multiple group growth model examples. |
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You can start from ex 6.18. |
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Evan Fishman posted on Wednesday, September 28, 2016 - 12:14 pm
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I'm looking to run a model that compares two cohorts of teachers (Cohorts 1 & 2) over 4 time points. At each time point, there are two continuous dependent variables (rating 1 & rating 2). There is missing data, and there is a covariate at times 3 and 4. Mainly, I want to examine the cohort x time interaction, and the time and cohort main effects. Simple slopes as well. Teachers are clustered within school, and schools are confounded within cohort (i.e., if school has more than 1 teacher, all teachers are in same cohort). Any help is much appreciated! |
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You get a lot of modeling flexibility by representing the cohorts by multiple groups. Use school as level 2 and teacher as level 1 where the 4*2 outcomes are spread out in wide format for the growth modeling. |
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