Hedges, L.V. (1998). Bayesian meta-analysis. In Statistical Analysis of Medical Data: New Developments (eds. B. Everitt and G. Dunn), Arnold, New York, pp. 251-276.Pitchforth, J. O., & Mengersen, K. L. (2013).
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(meta-analysis) Meta-analysis worksheet Reconstruction of individual patient data ▶ Clinical trials often publish Kaplan-Meier curves for each arm and hazard ratio with 95% CI ▶ If want to look at other metrics, would be great if had the individual patient data ▶ Turns out this can ...
meta-analysisSROC curveLyle D BroemelingBroemeling amp;amp; Associates Inc, Medical Lake, WA, USAAbstract: Determining the accuracy of a medical test is quite difficult because accuracy is an elusive parameter to estimate. A common scenario is estimating the true and false positive fractions from...
The primary purpose of this method is to allow meta-analytic researchers to control the contribution of each individual study to an estimated overall effect size though power prior. This is due to the consideration that not all studies included in a meta-analysis should be viewed as equally ...
Bayesian analysis for summary accuracy The obvious measure of test accuracy for a meta-analysis is the area under the SROC curve; however, since the TPR values tend to be concentrated over a relatively small range of FPR values, the entire SROC curve must be estimated by extrapolation to the...
This meta-analysis combines population-based surveys and data from the US Centers for Disease Control and Prevention’s Vision and Eye Health Surveillance
Second, data-derived prior distributions were developed based on relevant studies from a meta-analysis of ECMO for ARDS.1 The treatment effects in these previous studies were combined with the observed data from this trial in a ...
置信区间不可靠,那meta analysis为什么要用方差的倒数来做weight?frequentist有frequentist的好,bayesian也有bayesian的好。bayesian如果设flat prior,很大可能95%CI跟frequentist的95%CI区间数字一模一样,只是解释不一样。即使设flat prior, 也可能会导致shrinkage problem。 所以总结一句基于frequentist的CI“非常”不可靠呢...
With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or com