Report Quality of Generalized Linear Mixed Models in Psychology: A Systematic Review

Frontiers in Psychology

Rafael Alarcón¹  María J. Blanca¹  Roser Bono² 

[1] Department of Psychobiology and Behavioral Sciences Methodology, Faculty of Psychology, University of Malaga, Málaga, Spain;Department of Social Psychology and Quantitative Psychology, Faculty of Psychology, University of Barcelona, Barcelona, Spain;Institute of Neurosciences, University of Barcelona, Barcelona, Spain;

关键词: generalized linear mixed models;    systematic review;    empirical research;    report quality;    methodological review;   

DOI  :  10.3389/fpsyg.2021.666182

来源: Frontiers

【 摘 要 】

Generalized linear mixed models (GLMMs) estimate fixed and random effects and are especially useful when the dependent variable is binary, ordinal, count or quantitative but not normally distributed. They are also useful when the dependent variable involves repeated measures, since GLMMs can model autocorrelation. This study aimed to determine how and how often GLMMs are used in psychology and to summarize how the information about them is presented in published articles. Our focus in this respect was mainly on frequentist models. In order to review studies applying GLMMs in psychology we searched the Web of Science for articles published over the period 2014–2018. A total of 316 empirical articles were selected for trend study from 2014 to 2018. We then conducted a systematic review of 118 GLMM analyses from 80 empirical articles indexed in Journal Citation Reports during 2018 in order to evaluate report quality. Results showed that the use of GLMMs increased over time and that 86.4% of articles were published in first- or second-quartile journals. Although GLMMs have, in recent years, been increasingly used in psychology, most of the important information about them was not stated in the majority of articles. Report quality needs to be improved in line with current recommendations for the use of GLMMs.

【 授权许可】

CC BY