Malley, Paul (2009) Sensitivity methods for publication bias in a meta-analysis. PhD thesis, University of Warwick.

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Abstract

Meta-analysis is the statistical part of a systematic review. Many researchers have
used selection functions to model publication bias in a meta-analysis. The main
problem with this approach is that it is impossible to verify that the selection function
truly represents the selection process, and so the use of selection functions can only
be seen as part of a sensitivity analysis. In this thesis we present new methods that
involve selection functions that aim to make as few strong assumptions about selection
as possible, including the use of a non-parametric permutation test, and the use of a
step selection function. We also investigate the use of parametric selection functions
and suggest how researchers could use these as part of a sensitivity analysis, by looking
at a range of plausible values for the overall selection probability. As part of this
sensitivity analysis, we assess the effectiveness of the Bounds method as presented
by Henmi et al. Throughout the thesis we illustrate all methods with numerical
examples, including a meta-analysis investigating the effects of environmental tobacco
smoke on the risk of lung cancer in non-smokers.

Item Type:	Thesis or Dissertation (PhD)
Subjects:	Q Science > QA Mathematics
Library of Congress Subject Headings (LCSH):	Meta-analysis, Ranking and selection (Statistics)
Official Date:	October 2009
Dates:	Date Event October 2009 Submitted
Institution:	University of Warwick
Theses Department:	Department of Statistics
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Copas, John B.
Extent:	ix, 167 leaves : charts
Language:	eng

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