The effect of number of clusters and cluster size on statistical power and Type I error rates when testing random effects variance components in multilevel linear and logistic regression models-Reference-Cited by-同舟云学术

The effect of number of clusters and cluster size on statistical power and Type I error rates when testing random effects variance components in multilevel linear and logistic regression models

Published:2018-08-07 Issue:16 Volume:88 Page:3151-3163
ISSN:0094-9655
Container-title:Journal of Statistical Computation and Simulation
language:en
Short-container-title:Journal of Statistical Computation and Simulation

Author:

Austin Peter C.¹²³,Leckie George⁴

Affiliation:

1. Institute for Clinical Evaluative Sciences, Toronto, ON, Canada

2. Institute of Health Management, Policy and Evaluation, University of Toronto, Toronto, ON, Canada

3. Schulich Heart Research Program, Sunnybrook Research Institute, Toronto, ON, Canada

4. Centre for Multilevel Modelling, University of Bristol, Bristol, UK

Funder

Institute for Clinical Evaluative Sciences

Ontario Ministry of Health and Long-Term Care

Canadian Institutes of Health Research

Publisher

Informa UK Limited

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00949655.2018.1504945

Reference9 articles.

1. Determinants of intercultural adjustment among expatriate spouses

2. Multilevel Statistical Models

3. Partitioning Variation in Multilevel Models

4. Likelihood Ratio, Score, and Wald Tests in a Constrained Parameter Space

5. Multilevel Analysis

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