A tutorial for meta-analysis of diagnostic tests for low-prevalence diseases: Bayesian models and software
Author(s) / Creator(s)
Pambabay-Calero, Johny J.
Bauz-Olvera, Sergio A.
Nieto-Librero, Ana B.
Galindo-Villardón, Maria Purificación
Sánchez-García, Ana B.
Abstract / Description
Although measures such as sensitivity and specificity are used in the study of diagnostic test accuracy, these are not appropriate for integrating heterogeneous studies. Therefore, it is essential to assess in detail all related aspects prior to integrating a set of studies so that the correct model can then be selected. This work describes the scheme employed for making decisions regarding the use of the R, STATA and SAS statistical programs. We used the R Program Meta-Analysis of Diagnostic Accuracy package for determining the correlation between sensitivity and specificity. This package considers fixed, random and mixed effects models and provides excellent summaries and assesses heterogeneity. For selecting various cutoff points in the meta-analysis, we used the STATA module for meta-analytical integration of diagnostic test accuracy studies, which produces bivariate outputs for heterogeneity.
Keyword(s)
bivariate models heterogeneity meta-analysis statistical softwarePersistent Identifier
Date of first publication
2020-09-30
Journal title
Methodology
Volume
16
Issue
3
Page numbers
258–277
Publisher
PsychOpen GOLD
Publication status
publishedVersion
Review status
peerReviewed
Is version of
Citation
Pambabay-Calero, J. J., Bauz-Olvera, S. A., Nieto-Librero, A. B., Galindo-Villardón, M. P., & Sánchez-García, A. B. (2020). A tutorial for meta-analysis of diagnostic tests for low-prevalence diseases: Bayesian models and software. Methodology, 16(3), 258-277. https://doi.org/10.5964/meth.4015
-
meth.v16i3.4015.pdfAdobe PDF - 1MBMD5: 860aa8f982e45a9c63daa95cd3e7c629
-
There are no other versions of this object.
-
Author(s) / Creator(s)Pambabay-Calero, Johny J.
-
Author(s) / Creator(s)Bauz-Olvera, Sergio A.
-
Author(s) / Creator(s)Nieto-Librero, Ana B.
-
Author(s) / Creator(s)Galindo-Villardón, Maria Purificación
-
Author(s) / Creator(s)Sánchez-García, Ana B.
-
PsychArchives acquisition timestamp2022-04-14T11:24:44Z
-
Made available on2022-04-14T11:24:44Z
-
Date of first publication2020-09-30
-
Abstract / DescriptionAlthough measures such as sensitivity and specificity are used in the study of diagnostic test accuracy, these are not appropriate for integrating heterogeneous studies. Therefore, it is essential to assess in detail all related aspects prior to integrating a set of studies so that the correct model can then be selected. This work describes the scheme employed for making decisions regarding the use of the R, STATA and SAS statistical programs. We used the R Program Meta-Analysis of Diagnostic Accuracy package for determining the correlation between sensitivity and specificity. This package considers fixed, random and mixed effects models and provides excellent summaries and assesses heterogeneity. For selecting various cutoff points in the meta-analysis, we used the STATA module for meta-analytical integration of diagnostic test accuracy studies, which produces bivariate outputs for heterogeneity.en_US
-
Publication statuspublishedVersion
-
Review statuspeerReviewed
-
CitationPambabay-Calero, J. J., Bauz-Olvera, S. A., Nieto-Librero, A. B., Galindo-Villardón, M. P., & Sánchez-García, A. B. (2020). A tutorial for meta-analysis of diagnostic tests for low-prevalence diseases: Bayesian models and software. Methodology, 16(3), 258-277. https://doi.org/10.5964/meth.4015en_US
-
ISSN1614-2241
-
Persistent Identifierhttps://hdl.handle.net/20.500.12034/5696
-
Persistent Identifierhttps://doi.org/10.23668/psycharchives.6300
-
Language of contenteng
-
PublisherPsychOpen GOLD
-
Is version ofhttps://doi.org/10.5964/meth.4015
-
Is related tohttps://doi.org/10.23668/psycharchives.3485
-
Keyword(s)bivariate modelsen_US
-
Keyword(s)heterogeneityen_US
-
Keyword(s)meta-analysisen_US
-
Keyword(s)statistical softwareen_US
-
Dewey Decimal Classification number(s)150
-
TitleA tutorial for meta-analysis of diagnostic tests for low-prevalence diseases: Bayesian models and softwareen_US
-
DRO typearticle
-
Issue3
-
Journal titleMethodology
-
Page numbers258–277
-
Volume16
-
Visible tag(s)Version of Recorden_US