Zero-truncated modelling in a meta-analysis on suicide data after bariatric surgery
Zero-truncated modelling in a meta-analysis on suicide data after bariatric surgery
Meta-analysis is a well-established method for integrating results from several independent studies to estimate a common quantity of interest. However, meta-analysis is prone to selection bias, notably when particular studies are systematically excluded. This can lead to bias in estimating the quantity of interest. Motivated by a meta-analysis to estimate the rate of completed-suicide after bariatric surgery, where studies which reported no suicides were excluded, a novel zero-truncated count modeling approach was developed. This approach addresses heterogeneity, both observed and unobserved, through covariate and overdispersion modeling, respectively. Additionally, through the Horvitz-Thompson estimator, an approach is developed to estimate the number of excluded studies, a quantity of potential interest for researchers. Uncertainty quantification for both estimation of suicide rates and number of excluded studies is achieved through a parametric bootstrapping approach.
Capture-recapture, Horvitz-Thompson estimator, Parametric bootstrap, Zero-truncated regression model
Dennett, Layna Charlie
78f7f46c-406a-4e7f-b02f-e54ac3818d90
Overstall, Antony
c1d6c8bd-1c5f-49ee-a845-ec9ec7b20910
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
11 July 2025
Dennett, Layna Charlie
78f7f46c-406a-4e7f-b02f-e54ac3818d90
Overstall, Antony
c1d6c8bd-1c5f-49ee-a845-ec9ec7b20910
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Dennett, Layna Charlie, Overstall, Antony and Böhning, Dankmar
(2025)
Zero-truncated modelling in a meta-analysis on suicide data after bariatric surgery.
The American Statistician.
(doi:10.1080/00031305.2025.2507380).
Abstract
Meta-analysis is a well-established method for integrating results from several independent studies to estimate a common quantity of interest. However, meta-analysis is prone to selection bias, notably when particular studies are systematically excluded. This can lead to bias in estimating the quantity of interest. Motivated by a meta-analysis to estimate the rate of completed-suicide after bariatric surgery, where studies which reported no suicides were excluded, a novel zero-truncated count modeling approach was developed. This approach addresses heterogeneity, both observed and unobserved, through covariate and overdispersion modeling, respectively. Additionally, through the Horvitz-Thompson estimator, an approach is developed to estimate the number of excluded studies, a quantity of potential interest for researchers. Uncertainty quantification for both estimation of suicide rates and number of excluded studies is achieved through a parametric bootstrapping approach.
Text
Zero-Truncated Modelling in a Meta-Analysis on Suicide Data after Bariatric Surgery (1)
- Accepted Manuscript
Text
Meta_analysis_of_suicide_rate_v4
- Other
Restricted to Repository staff only
Request a copy
More information
Accepted/In Press date: 27 April 2025
e-pub ahead of print date: 20 May 2025
Published date: 11 July 2025
Keywords:
Capture-recapture, Horvitz-Thompson estimator, Parametric bootstrap, Zero-truncated regression model
Identifiers
Local EPrints ID: 501701
URI: http://eprints.soton.ac.uk/id/eprint/501701
ISSN: 0003-1305
PURE UUID: f83ca87c-896d-4caf-bc30-a37e773343ca
Catalogue record
Date deposited: 06 Jun 2025 16:39
Last modified: 03 Sep 2025 02:03
Export record
Altmetrics
Contributors
Author:
Layna Charlie Dennett
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics