I have just spent a semester teaching multilevel modeling, and in the R codes I provided, I usually use the pipe operator (%>%). For example, to compute the cluster means, we can do

Load packages Data Polychoric Correlations lavaan OpenMx Weighted Least Squares Estimation One-factor model Standard Errors Final thoughts Recently I was working on a revision for a paper that involves structural equation modeling with categorical observed variables, and it uses a robust variant of weighted least square (also called asymptotic distribution free) estimators.

Define True Model and Simulate Some Data Define Log-Likelihood Function Defining \(\mathcal{l}(\boldsymbol{\mathbf{\Sigma}}; S)\) in R: MLE Asymptotic Standard Errors Using expected information Observed information (using Hessian) MLM/MLMV MLR Bibliography In our lab meeting I’m going to present the article by Maydeu-Olivares (2017), which talked about standard errors (SEs) of the maximum likelihood estimators (MLEs) in SEM models.

The Problem Demonstration Group mean centering with lme4 Same analyses with Bayesian using brms Group mean centering treating group means as latent variables With random slopes Using the Full Data With lme4 With Bayesian taking into account the unreliability Bibliography This post is updated on 2020-02-04 with cleaner and more efficient STAN code.

Complexity of MLM Information Criteria Example Selecting Fixed Effects How to Choose Between AIC and BIC? Including Lv-2 Predictors Workflow Regularization Bibliography In social sciences, many times we use statistical methods to answer well-defined research questions that are derived from some theory or previous research.

Quasi-Bayesian/Monte Carlo CI With the mediation Package
Analytical Approaches for CI With the RMediation Package
Distribution of Product of Coefficients
Asymptotic Normal CI
Case Bootstrap
Bootstrap CI
Fully Bayesian Approach With rstan
Posterior (Credible) Intervals
Summary Table of Different CIs:
Bibliography
The data are from the mediation package, which are simulated data with the source of the Education Longitudinal Study of 2002.

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