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EZalberta posted on Tuesday, November 23, 2010  11:55 pm



Hi, I am pretty new to Mplus and to structural equation modeling (SEM) in general. I have a dataset with cross sectionaltime series data structure: a list of variables for 170 countries measured across 20 years. These variables include: dependent variable, which is a count variable; and variables which are supposed to be indicators of 4 latent variables; and finally a set of control variables. I want to estimate both the independent and interaction effects of the 4 latent variables on the count variable, controlling for the control variables. I wonder whether this type of analysis could be done using structural equation modeling, which type of SEM I should use, and whether MPLUS can achieve this. Thanks in advance for your help! 


It sounds like you want to regress a count variable on a set of observed and latent exogenous variables and their interactions. That can be done in Mplus. Each interaction between two latent variables or a latent variable and an observed variable requires one dimension of integration. A model with more than four dimensions of integration is not recommended. 

EZalberta posted on Wednesday, November 24, 2010  5:09 pm



Thanks Linda. This is very helpful! The interactions in my estimation will be mostly twoway interactions among the 4 latent variables, which means theoretically there can be as many as 6 twoway interactions. Can MPLUS accommodate this many interactions? Also panel data regression can be estimated by fixeffects and random effects models. If I want to estimate three models: countrylevel fixed effect model, country and year twoway fixed effects model, and random effect model; can MPLUS do all three? And can you refer me to some example syntax? Thank you! 

EZalberta posted on Wednesday, November 24, 2010  5:23 pm



And both my independent variables and dependent variables are measured on 20 time points. I understand for panel data with only a few waves, where for example, independent variable is measured in wave 1 and dependent variables measured in wave 2, SEM can be easily estimated. But for my case, both independent variables and dependent variables are measured in 20 waves, where I hope to use independent variables measured in time t1 to estimate dependent variable in time t, how shall I specify the model in MPLUS? If there is no latent variables, I can simply use xtpoisson in stata to do the job, the existence of latent variables just complicates the estimation. Hope MPLUS is more powerful on this type of analysis. Thanks! 


A model with more than four dimensions of integration is not recommended. This would be four latent variable interactions. It is not likely that all are signficant so I would investigate that and include on the ones that are significant. See the examples chapters of the user's guide. You can use the ON option as follows: y2y20 PON x1x19; 


Linda and Bengt, I have run across a very interesting paper that purports to model time series cross sectional data as a multilevel SEM. What makes this stand out is that the data for each time period is cross sectional. That is, a unique sample of respondents is collected for each time period without any overlap of Rs. The link is below. Can I do anything similar to this in MPLUS? http://business.illinois.edu/ba/seminars/2013/Fall/park_paper.pdf Thanks, Tom 


Tom This estimation method is not available yet in Mplus. Some time series possibilities are discussed in http://mplus.fss.uu.nl/files/2012/09/MplusUsersMeeting2012TihomirAsparouhov.pdf 

Thomas Eagle posted on Wednesday, October 15, 2014  11:15 pm



Thank you, Tihomir. I'll look the slides over. Tom 

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