2014
DOI: 10.1371/journal.pone.0112653
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Methodological Quality and Reporting of Generalized Linear Mixed Models in Clinical Medicine (2000–2012): A Systematic Review

Abstract: BackgroundModeling count and binary data collected in hierarchical designs have increased the use of Generalized Linear Mixed Models (GLMMs) in medicine. This article presents a systematic review of the application and quality of results and information reported from GLMMs in the field of clinical medicine.MethodsA search using the Web of Science database was performed for published original articles in medical journals from 2000 to 2012. The search strategy included the topic “generalized linear mixed models”… Show more

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Cited by 89 publications
(96 citation statements)
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“…On the basis of the works of Bolker (2009), Thiele (2012) and Casals (2014), a list of relevant information and basic characteristics of the logistic mixed model was reported. The model expression for team i in its j th games is the following: logit (π ij )= log(π ij /1- π ij )= X ij β+ ui where π i is the probability of winning a match and X includes all independent variables of interest.…”
Section: Methodsmentioning
confidence: 99%
“…On the basis of the works of Bolker (2009), Thiele (2012) and Casals (2014), a list of relevant information and basic characteristics of the logistic mixed model was reported. The model expression for team i in its j th games is the following: logit (π ij )= log(π ij /1- π ij )= X ij β+ ui where π i is the probability of winning a match and X includes all independent variables of interest.…”
Section: Methodsmentioning
confidence: 99%
“…For variables with skewed distributions, the Mann-Whitney U test and the Wilcoxon signed rank test were applied instead. To accommodate the correlation of observations due to the repeated measures (pre- and post-intervention testing) and the clustering of individuals within the 10 randomly selected communes, multilevel generalized linear mixed models with random effects (participants and communes) were fitted to determine the impacts of intervention on changes in outcome variables over time and between groups [32, 33], while accounting for the effects of potential confounding factors (age, sex, education level, relationship status, occupation, smoking status and alcohol consumption). All statistical analyses were performed in the SPSS package version 21.…”
Section: Methodsmentioning
confidence: 99%
“…The General Linear Model (GLM) (see [1]) is one of the most widely applied statistical methods, with applications common in psychology [2], education [3], medicine [4], business [5], and several other disciplines. The GLM's popularity in applied research is likely due to a combination of the model's interpretability and flexibility, as well as easy availability through R [6] and commercial statistical softwares (e.g., SAS, SPSS, etc.).…”
Section: Motivationmentioning
confidence: 99%