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Network meta-analysis of diagnostic test accuracy (NMA-DTA) is a relatively new field, involving combining evidence across studies to evaluate and compare the accuracy of different tests for a given condition. However, the methods proposed…

Methodology · Statistics 2026-04-23 Efthymia Derezea , Gabriel Rogers , Nicky J Welton , Hayley E Jones

Meta-analyses of diagnostic test accuracy (DTA) studies have been gathering attention in research in clinical epidemiology and health technology development, and bivariate random-effects model is becoming a standard tool. However, standard…

Methodology · Statistics 2020-06-19 Tsubasa Ito , Shonosuke Sugasawa

In diagnostic test accuracy meta-analysis (DTA-MA), standard inference methods using bivariate random-effects models for jointly synthesizing sensitivity and specificity can be sensitive to outlying studies and may yield misleading…

Methodology · Statistics 2026-05-01 Kotaro Sasaki , Hisashi Noma , Theodoros Evrenoglou

Standard (network) meta-analysis methods for medical test accuracy evaluation analyse the data separately for each test threshold - wasting data - unless every study reports all thresholds. Previously proposed "multiple threshold" models…

Rich meta-epidemiological data sets have been collected to explore associations between intervention effect estimates and study-level characteristics. Welton et al. proposed models for the analysis of meta-epidemiological data, but these…

Applications · Statistics 2017-11-28 Kirsty Rhodes , David Mawdsley , Rebecca Turner , Hayley Jones , Jelena Savovic , Julian Higgins

The present study investigates the performance of several statistical tests to detect publication bias in diagnostic meta-analysis by means of simulation. While bivariate models should be used to pool data from primary studies in diagnostic…

Methodology · Statistics 2022-11-24 Paul-Christian Bürkner , Philipp Doebler

It is recommended that measures of between-study effect heterogeneity be reported when conducting individual-participant data meta-analyses (IPD-MA). Methods exist to quantify inconsistency between trials via I^2 (the percentage of…

We outline a Bayesian model-averaged meta-analysis for standardized mean differences in order to quantify evidence for both treatment effectiveness $\delta$ and across-study heterogeneity $\tau$. We construct four competing models by…

Introduction: Despite their applicability, statistical models used for the meta-analysis of test accuracy require specialised knowledge to implement, with the necessary level of expertise having recently increased. This is due to the…

Applications · Statistics 2022-11-16 Enzo Cerullo , Alex J. Sutton , Hayley E. Jones , Olivia Wu , Terry J. Quinn , Nicola J. Cooper

Meta-analysis seeks to combine the results of several experiments in order to improve the accuracy of decisions. It is common to use a test for homogeneity to determine if the results of the several experiments are sufficiently similar to…

Methodology · Statistics 2009-08-01 Elena Kulinskaya , Michael B. Dollinger , Kirsten Bjørkestøl

Heterogeneity is a hallmark of complex diseases. Regression-based heterogeneity analysis, which is directly concerned with outcome-feature relationships, has led to a deeper understanding of disease biology. Such an analysis identifies the…

Methodology · Statistics 2022-11-29 Ziye Luo , Xinyue Yao , Yifan Sun , Xinyan Fan

Meta-analyses are commonly performed based on random-effects models, while in certain cases one might also argue in favour of a common-effect model. One such case may be given by the example of two "study twins" that are performed according…

Methodology · Statistics 2024-09-04 Christian Röver , Tim Friede

Meta-analyses of diagnostic test accuracy (DTA) studies have been gaining prominence in research in clinical epidemiology and health technology development. In these DTA meta-analyses, some studies may have markedly different…

Methodology · Statistics 2021-07-14 Yuki Matsushima , Hisashi Noma , Tomohide Yamada , Toshi A. Furukawa

[See paper for full abstract] Meta-analysis is a crucial tool for answering scientific questions. It is usually conducted on a relatively small amount of ``trusted'' data -- ideally from randomized, controlled trials -- which allow causal…

Machine Learning · Statistics 2024-07-15 Shiva Kaul , Geoffrey J. Gordon

Quantifying the heterogeneity is an important issue in meta-analysis, and among the existing measures, the $I^2$ statistic is most commonly used. In this paper, we first illustrate with a simple example that the $I^2$ statistic is heavily…

Methodology · Statistics 2025-06-10 Ke Yang , Enxuan Lin , Wangli Xu , Liping Zhu , Tiejun Tong

Patients in clinical studies often exhibit heterogeneous treatment effect (HTE). Classical subgroup analyses provide inferential tools to test for effect modification, while modern machine learning methods estimate the Conditional Average…

Applications · Statistics 2026-01-05 Nan Miles Xi , Xin Huang , Lin Wang

Diagnostic accuracy studies assess sensitivity and specificity of a new index test in relation to an established comparator or the reference standard. The development and selection of the index test is usually assumed to be conducted prior…

Methodology · Statistics 2022-08-30 Max Westphal , Antonia Zapf

Objective: We investigated the associations between risk of bias judgments from Cochrane reviews for sequence generation, allocation concealment and blinding and between-trial heterogeneity. Study Design and Setting: Bayesian hierarchical…

Applications · Statistics 2017-11-28 Kirsty Rhodes , Rebecca Turner , Jelena Savović , Hayley Jones , David Mawdsley , Julian Higgins

Meta-analysis of diagnostic test accuracy (DTA) is the powerful statistical method for synthesizing and evaluating the diagnostic capacity of the medical tests and has been extensively used by clinical physicians and healthcare…

Applications · Statistics 2023-03-07 Shosuke Mizutani , Yi Zhou , Yu-Shi Tian , Tatsuya Takagi , Tadayasu Ohkubo , Satoshi Hattori

Case-mix heterogeneity across studies complicates meta-analyses. As a result of this, treatments that are equally effective on patient subgroups may appear to have different effectiveness on patient populations with different case mix. It…

Applications · Statistics 2021-08-25 Tat-Thang Vo , Raphael Porcher , Anna Chaimani , Stijn Vansteelandt
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