Load Packages Data Hypothetical Research Question Distinguishable Dyads Indistinguishable Dyads Model Comparison Using SEM Distinguishable Dyads Indistinguishable Dyads Every time I teach multilevel modeling (MLM) at USC, I have students interested in running the actor partner independence model (APIM) using dyadic model.
One thing that I always felt uncomfortable in multilevel modeling (MLM) is the concept of a unit-specific (US)/subject-specific model vs. a population-average (PA) model. I’ve come across it several times, but for some reason I haven’t really made an effort to fully understand it.
This article shows that the previously proposed between-level composite reliability can provide overly optimistic reliability coefficient because it ignores one major source of error, namely the sampling error of cluster means. To obtain more accurate reliability information for multilevel data, this article proposes alternative reliability indices that correctly account for the different sources of measurement error.
Although many methodologists and professional organizations have urged applied researchers to compute and report effect size measures accompanying tests of statistical significance, discussions on obtaining confidence interval (CI) for effect size …
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.
Data in behavioral research usually follow a clustered structure, such as students nested in schools, participants nested in intervention groups, siblings within families, and, in longitudinal studies, repeated measures nested within persons. In this …
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.