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The identity of two meta-analytic likelihoods and the ignorability of double-zero studies

The identity of two meta-analytic likelihoods and the ignorability of double-zero studies
The identity of two meta-analytic likelihoods and the ignorability of double-zero studies
In meta-analysis, the conventional two-stage approach computes an effect estimate for each study in the first stage and proceeds with the analysis of effect estimates in the second stage. For counts of events as outcome, the risk ratio is often the effect measure of choice. However, if the meta-analysis includes many studies with no events the conventional method breaks down. As an alternative one-stage approach a Poisson regression model and a conditional binomial model can be considered where no event studies do not cause problems. The conditional binomial model excludes double-zero studies, whereas this is seemingly not the case for the Poisson regression approach. However, we show here that both models lead to the same likelihood inference and double-zero studies (in contrast to single-zero studies) do not contribute in either case to the likelihood.
1465-4644
Bohning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Sangnawakij, Patarawan
3baba4ef-a7c4-42d4-b9c2-a363ad9981a1
Bohning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Sangnawakij, Patarawan
3baba4ef-a7c4-42d4-b9c2-a363ad9981a1

Bohning, Dankmar and Sangnawakij, Patarawan (2020) The identity of two meta-analytic likelihoods and the ignorability of double-zero studies. Biostatistics.

Record type: Article

Abstract

In meta-analysis, the conventional two-stage approach computes an effect estimate for each study in the first stage and proceeds with the analysis of effect estimates in the second stage. For counts of events as outcome, the risk ratio is often the effect measure of choice. However, if the meta-analysis includes many studies with no events the conventional method breaks down. As an alternative one-stage approach a Poisson regression model and a conditional binomial model can be considered where no event studies do not cause problems. The conditional binomial model excludes double-zero studies, whereas this is seemingly not the case for the Poisson regression approach. However, we show here that both models lead to the same likelihood inference and double-zero studies (in contrast to single-zero studies) do not contribute in either case to the likelihood.

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Accepted/In Press date: 17 January 2020
e-pub ahead of print date: 17 January 2020

Identifiers

Local EPrints ID: 438207
URI: http://eprints.soton.ac.uk/id/eprint/438207
ISSN: 1465-4644
PURE UUID: 5ba0df0f-f396-43b2-a6b1-c745132224fb
ORCID for Dankmar Bohning: ORCID iD orcid.org/0000-0003-0638-7106

Catalogue record

Date deposited: 04 Mar 2020 17:30
Last modified: 18 Feb 2021 17:17

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Contributors

Author: Dankmar Bohning ORCID iD
Author: Patarawan Sangnawakij

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