Various varying variances: The challenge of nuisance parameters to the practising biostatistician

Stephen Senn

doi:10.1177/0962280214520728

Various varying variances: The challenge of nuisance parameters to the practising biostatistician

Stephen Senn^*

^*Corresponding author for this work

Competence Center for Methodology and Statistics

Research output: Contribution to journal › Article › Research › peer-review

12 Citations (Scopus)

Abstract

The 1997 Biometrics paper by Mike Kenward and James Roger has become a citation classic (more than 1260 citations by End June 2013 according to Google Scholar) and the solution that they proposed to deal with the problem of significance tests of fixed effects in REML models is now incorporated in many software packages and accepted by all biostatisticians as the method of choice. Nevertheless, it does not solve all problems, since there is more to analysis than just significance and since the problems that models with more than one variance pose arise in many contexts. In this paper, I discuss some problems and applications and make some tentative suggestions as to how they may be tackled. My excuse for raising problems I do not solve is that it may inspire James and Mike to complete what they started.

Original language	English
Pages (from-to)	403-419
Number of pages	17
Journal	Statistical Methods in Medical Research
Volume	24
Issue number	4
DOIs	https://doi.org/10.1177/0962280214520728
Publication status	Published - 25 Aug 2015

Keywords

Analysis of covariance
Components of Variance
Gauss-Markov theorem
History of statistics
Mixed models
REML

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10.1177/0962280214520728

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abstract = "The 1997 Biometrics paper by Mike Kenward and James Roger has become a citation classic (more than 1260 citations by End June 2013 according to Google Scholar) and the solution that they proposed to deal with the problem of significance tests of fixed effects in REML models is now incorporated in many software packages and accepted by all biostatisticians as the method of choice. Nevertheless, it does not solve all problems, since there is more to analysis than just significance and since the problems that models with more than one variance pose arise in many contexts. In this paper, I discuss some problems and applications and make some tentative suggestions as to how they may be tackled. My excuse for raising problems I do not solve is that it may inspire James and Mike to complete what they started.",

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Various varying variances: The challenge of nuisance parameters to the practising biostatistician

Abstract

Keywords

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