Use of between-within degrees of freedom as an alternative to the Kenward–Roger method for small-sample inference in generalized linear mixed modeling of clustered count data-Reference-Cited by-同舟云学术

Use of between-within degrees of freedom as an alternative to the Kenward–Roger method for small-sample inference in generalized linear mixed modeling of clustered count data

Published:2021-09-30 Issue: Volume: Page:1-11
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Staggs Vincent S.¹²^ORCID,Feldman Keith²³

Affiliation:

1. Biostatistics & Epidemiology Core, Children’s Mercy Kansas City, Kansas City, MO, USA;

2. Department of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA;

3. Health Services & Outcomes Research, Children’s Mercy Kansas City, Kansas City, MO, USA

Publisher

Informa UK Limited

Subject

Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2021.1982976

Reference19 articles.

1. Small sample estimation properties of longitudinal count models

2. Mixed Models

3. Performance of analytical methods for overdispersed counts in cluster randomized trials: Sample size, degree of clustering and imbalance

4. SimCorrMix: Simulation of Correlated Data with Multiple Variable Types Including Continuous and Count Mixture Distributions

5. Confidence, prediction, and tolerance in linear mixed models

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