The models presented here add grouping variables to “baseline” models. Code for models with and without measurement invariance across groups is available, as is code for different types of measurement invariance available with LPA.

LCA: LCA with a grouping variable and without measurement variance

This code fits a 4-class, latent-class model for marijuana use and attitudes using 7 binary indicators of the latent class variable. It includes a grouping variable for year, and observations came from 3 different years. Measurement invariance across groups is not imposed resulting in an unrestricted latent class model with multiple groups.

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LPA: LPA with a grouping variable with measurement invariance across means and variances

Description This code fits a baseline, latent-profile model to identify and describe profiles of financial stress responses. It also imposes measurement invariance across the groups with means and variances equal. This code corresponds to the research paper titled “Financial stress response profiles and psychosocial functioning in low-income parents” published in Journal of Family Psychology in 2018. The paper can be found here: https://pubmed.ncbi.nlm.nih.gov/29878812/ Software Downloads Mplus Model Features Model Category Your Content Goes Here Model Type Your Content Goes Here Indicator Type Your Content Goes Here Software Options Your Content Goes Here Measurement Invariance Your Content Goes Here Approach to...

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LPA: LPA with a grouping variable without measurement invariance

Description This code fits a baseline, latent-profile model to identify and describe profiles of financial stress responses. It doesn’t impose measurement invariance across the groups. This model is similar to the model in the research paper titled “Financial stress response profiles and psychosocial functioning in low-income parents” published in Journal of Family Psychology in 2018. One key difference is that this model DOES NOT impose measurement invariance while the model in the paper DOES impose measurement invariance. The paper can be found here: https://pubmed.ncbi.nlm.nih.gov/29878812/ The code for the model in the paper (i.e. with measurement invariance) can be found here....

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