Generalized Linear Mixed-Effects Modeling Programs in R for Binary Outcomes

We review, examine the performance, and discuss the relative strengths and weaknesses of various R functions for the estimation of generalized linear mixed-effects models (GLMMs) for binary outcomes. The R functions reviewed include glmer in the package lme4, hglm2 in the package hglm, MCMCglmm in the package MCMCglmm, and inla in the package INLA. We illustrate the use of these functions through an empirical example and provide sample code.

• Publication year

  2018

• Venue

  Structural Equation Modeling: A Multidisciplinary Journal

• Publication date

  2018-08-02

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1080/10705511.2018.1500141
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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