What is it about?
Traces the history of attempts to deal with the fact that variances vary not just systematically but also randomly and speculates about lines of future research.
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Why is it important?
Explores a connection between analysis of covariance and mixed models to draw some lessons about statistical modelling when nuisance parameters are influential and degrees of freedom are scarce.
Perspectives
A tribute to James Roger on his retirement. My paper was inspired by James's important work with Mike Kenward (Biometrics, 1997) fixing REML to correct inferences for fixed effect parameters.
Professor Stephen J Senn
Consultant Statistician
Read the Original
This page is a summary of: Various varying variances: The challenge of nuisance parameters to the practising biostatistician, Statistical Methods in Medical Research, February 2014, SAGE Publications,
DOI: 10.1177/0962280214520728.
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