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Published in 2017 at "Statistics in medicine"
DOI: 10.1002/sim.7313
Abstract: In a bivariate meta-analysis, the number of diagnostic studies involved is often very low so that frequentist methods may result in problems. Using Bayesian inference is particularly attractive as informative priors that add a small…
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Keywords:
analysis;
bayesian bivariate;
bivariate meta;
meta analysis ... See more keywords
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Published in 2022 at "Gynecologic oncology"
DOI: 10.1016/j.ygyno.2022.03.026
Abstract: OBJECTIVE To optimize the use of confirmatory endoscopic exams (cystoscopy/proctoscopy) in the staging of locally advanced cervical cancer (LACC), the present study evaluates the predictive value of radiological exams (CT and MRI) to detect bladder/rectum…
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Keywords:
bivariate meta;
prevalence;
invasion;
cervical cancer ... See more keywords
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Published in 2019 at "Statistics"
DOI: 10.1080/02331888.2019.1581782
Abstract: ABSTRACT We propose a bivariate Farlie–Gumbel–Morgenstern (FGM) copula model for bivariate meta-analysis, and develop a maximum likelihood estimator for the common mean vector. With the aid of novel mathematical identities for the FGM copula, we…
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Keywords:
common mean;
bivariate;
bivariate meta;
fgm copula ... See more keywords
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Published in 2022 at "Symmetry"
DOI: 10.3390/sym14020186
Abstract: Traditional bivariate meta-analyses adopt the bivariate normal model. As the bivariate normal distribution produces symmetric dependence, it is not flexible enough to describe the true dependence structure of real meta-analyses. As an alternative to the…
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Keywords:
copula based;
bivariate;
bivariate meta;
meta analyses ... See more keywords