Learn xxM

The best way to learn multilevel structural equation modeling in xxM is to work through concrete examples. This page will lead you through different examples of linear mixed effects (lme) models, traditional multilevel models (MLM), and multilevel structural equation models (ML-SEM). Each example includes a path-diagram, complete model specification using scalar equations and matrices and complete specification of the model using xxM. Log and output of interactive session of fitting xxM models are also included.

First time users should begin with the “Hello xxM” example which describes everything you need to know about specifying a “two level – bivariate mixed-effects model”. Once you understand how models are ML-SEM models are specified in xxM, you could work through examples similar to your own data.

Name Source Data Levels Latent variable Random slope Structure Model LME
Hello xxM Mehta Simulated 2 No No Nested Bivariate random-intercepts model Yes
Stuff to dye for Bates Dyestuff 2 No No Nested Random-intercepts model Yes
Strong stuff Bates Pastes 3 No No Nested Random-intercepts model Yes
Big bugs Bates Penicillin 3 No No Crossed Random-intercepts model Yes
Reading to learn Branum-Martin Reading 2 No Yes Nested Random-slope for a continuous covariate Yes
Boys & Girls Goldstein GCSEMV 2 No No Nested Random-slope for a categorical covariate Yes
Feeling better – long Hedeker Reisby 2 No Yes Longitudinal Linear growth curve model Yes
Feeling better – wide Hedeker Reisby 1 Yes Yes Longitudinal Latent growth curve model No
Learning to read Mehta Reading 2 Yes No Nested Two-level Confirmatory Factor Analysis No
Pretty faces Wickham Faces 3 No No Crossed bivariate cross-classified model Yes
Quality schools or effective teachers Mehta Simulated 3 Yes No Nested Across-level latent variable regression No
Two-level CFA with random-slope Mehta Simulated 2 Yes Yes Nested Random slopes with latent dependent variable No