Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 1,505

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

A hierarchical regression approach to meta‐analysis of diagnostic test accuracy evaluations

Rutter, Carolyn M., Gatsonis, Constantine A.·2001·Statistics in Medicine
DOI 10.1002/sim.942
Open this paper in CoChat — free account

Abstract

An important quality of meta‐analytic models for research synthesis is their ability to account for both within‐ and between‐study variability. Currently available meta‐analytic approaches for studies of diagnostic test accuracy work primarily within a fixed‐effects framework. In this paper we describe a hierarchical regression model for meta‐analysis of studies reporting estimates of test sensitivity and specificity. The model allows more between‐ and within‐study variability than fixed‐effect approaches, by allowing both test stringency and test accuracy to vary across studies. It is also possible to examine the effects of study specific covariates. Estimates are computed using Markov Chain Monte Carlo simulation with publicly available software (BUGS). This estimation method allows flexibility in the choice of summary statistics. We demonstrate the advantages of this modelling approach using a recently published meta‐analysis comparing three tests used to detect nodal metastasis of cervical cancer. Copyright © 2001 John Wiley & Sons, Ltd.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/sim.942

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

Metadata

Authors
Rutter, C. M., & Gatsonis, C. A.
Venue
Statistics in Medicine
Publisher
Wiley
Published
2001-09-05
Volume
20
Issue
19
Pages
2865-2884
ISSN
  • 0277-6715 (ISSN-L)
  • 1097-0258
DOI
10.1002/sim.942
OpenAlex
W2151047141
Cited by
1,505
References
2
FWCI
6.98
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.