ERIC Number: EJ1037092
Record Type: Journal
Publication Date: 2014-Jun
Abstractor: As Provided
Reference Count: 13
Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models
Wagler, Amy E.
Journal of Educational and Behavioral Statistics, v39 n3 p167-179 Jun 2014
Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for estimating the heterogeneity due to clustering on a scale that is easy to interpret. The performance of the proposed asymptotic intervals and percentile bootstrap intervals are compared by simulations and in an application.
Descriptors: Hierarchical Linear Modeling, Cluster Grouping, Heterogeneous Grouping, Monte Carlo Methods, Reading, Scores, Regression (Statistics), Intervals, Computation, Simulation
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Sponsor: National Institute on Minority Health and Health Disparities (NIMHD)
Authoring Institution: N/A
IES Grant or Contract Numbers: G12MD007592