Skip to main content

Research Repository

Advanced Search

Response transformations for random effect and variance component models

Almohaimeed, Amani; Einbeck, Jochen

Response transformations for random effect and variance component models Thumbnail


Authors

Amani Almohaimeed



Abstract

Random effect models have been popularly used as a mainstream statistical technique over several decades; and the same can be said for response transformation models such as the Box–Cox transformation. The latter aims at ensuring that the assumptions of normality and of homoscedasticity of the response distribution are fulfilled, which are essential conditions for inference based on a linear model or a linear mixed model. However, methodology for response transformation and simultaneous inclusion of random effects has been developed and implemented only scarcely, and is so far restricted to Gaussian random effects. We develop such methodology, thereby not requiring parametric assumptions on the distribution of the random effects. This is achieved by extending the ‘Nonparametric Maximum Likelihood’ towards a ‘Nonparametric profile maximum likelihood’ technique, allowing to deal with overdispersion as well as two-level data scenarios.

Citation

Almohaimeed, A., & Einbeck, J. (2022). Response transformations for random effect and variance component models. Statistical Modelling, 22(4), 297-326. https://doi.org/10.1177/1471082x20966919

Journal Article Type Article
Acceptance Date Sep 28, 2020
Online Publication Date Dec 13, 2020
Publication Date Aug 1, 2022
Deposit Date Jan 20, 2021
Publicly Available Date Mar 28, 2024
Journal Statistical Modelling
Print ISSN 1471-082X
Electronic ISSN 1477-0342
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 22
Issue 4
Pages 297-326
DOI https://doi.org/10.1177/1471082x20966919
Keywords Box-Cox transformation, Random effects model, variance component model, nonparametric maximum likelihood, EM algorithm

Files

Accepted Journal Article (405 Kb)
PDF

Copyright Statement
Almohaimeed A, Einbeck J. Response transformations for random effect and variance component models. Statistical Modelling. 2022;22(4):297-326. doi:10.1177/1471082X20966919





You might also like



Downloadable Citations