Stata regress if1/31/2024 They extended the statistic to account for the correlation between sensitivity and specificity yielding a joint measure of heterogeneity. Zhou and Dendukuri proposed a univariate I 2 statistic that accounts for the mean-variance relationship across studies. This could lead to an incorrect conclusion of very high heterogeneity. Hence, heterogeneity statistics based on the normal-normal model tend to underestimate the expected value of the within-study variance resulting in high values of I 2. The fact that diagnostic data sets are binomial implies that the within-study variance in sensitivity and specificity parameters is a function of the mean parameters. ![]() Therefore, in meta-analysis of DTA separate statistics for sensitivity and specificity are computed. The statistic is based on the normal-normal model and was defined for univariate meta-analysis. The proportion of total unexplained variation due to between-study heterogeneity is usually quantified using the I 2 statistic by Higgins and Thompson. The two models incorporate covariates differently though they have been shown to be equivalent when no covariates are included. The two most commonly used statistical models for pooling of DTA data are the hierarchical summary receiver operating characteristic model (HSROC) and the bivariate random-effects meta-analysis model (BRMA). Hence, availability and dissemination of appropriate and optimal statistical methods in a robust and user-friendly program is quintessential. Scientists in the fields of public health, epidemiology or clinical research often do not have advanced statistical and/or programming skills. These models are relatively complex requiring expertise both in GLMMs and statistical programming. Generalized linear mixed models (GLMM) are therefore recommended. Moreover, the sample variance of sensitivity/specificity is a function of the sample mean and ignoring this mean-variance relationship may bias the summary estimate and its variance. 0/1, when the sample sizes or when the number of studies are small. These include poor statistical properties when sensitivity and/or specificity are close to the margins i.e. Meta-analysis of diagnostic test accuracy (DTA) studies using approximate methods such as the normal-normal model has several challenges. ![]() The Creative Commons Public Domain Dedication waiver ( ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
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