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

10 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

Access to Document

10.1177/0962280214520728

Cite this

@article{ce7e6c579bbd4192b8d9b4891506a112,

title = "Various varying variances: The challenge of nuisance parameters to the practising biostatistician",

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.",

keywords = "Analysis of covariance, Components of Variance, Gauss-Markov theorem, History of statistics, Mixed models, REML",

author = "Stephen Senn",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2014.",

year = "2015",

month = aug,

day = "25",

doi = "10.1177/0962280214520728",

language = "English",

volume = "24",

pages = "403--419",

journal = "Statistical Methods in Medical Research",

issn = "0962-2802",

publisher = "SAGE Publications Ltd",

number = "4",

}

TY - JOUR

T1 - Various varying variances

T2 - The challenge of nuisance parameters to the practising biostatistician

AU - Senn, Stephen

N1 - Publisher Copyright: © The Author(s) 2014.

PY - 2015/8/25

Y1 - 2015/8/25

N2 - 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.

AB - 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.

KW - Analysis of covariance

KW - Components of Variance

KW - Gauss-Markov theorem

KW - History of statistics

KW - Mixed models

KW - REML

UR - http://www.scopus.com/inward/record.url?scp=84937842247&partnerID=8YFLogxK

U2 - 10.1177/0962280214520728

DO - 10.1177/0962280214520728

M3 - Article

C2 - 24492794

AN - SCOPUS:84937842247

VL - 24

SP - 403

EP - 419

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

SN - 0962-2802

IS - 4

ER -

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

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this