Confidence Distributions and a Unifying Framework for Meta-Analysis

By Min‐ge Xie, Kesar Singh, William E. Strawderman. 2011

144 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9d903145e1fe0b6c72b856281ce9780f9ba4b254

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In Statistics and Probability

Citations in the corpus

Conducting indirect-treatment-comparison and network-meta-analysis studies: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 2. (2011, background): “Potential approaches include confidence distributions and scorebased confidence intervals [54,55].”
Generalized fiducial inference for normal linear mixed models (2012, background): “We evaluate the quality of the simulated generalized fiducial distribution based on the quality of the confidence intervals - a concept analogous to confidence distributions [53, 63].”
Generalized Fiducial Inference: A Review and New Results (2016, background): “…approach is fusion learning: its ability to combine information from disparate sources with deep implications for meta analysis (Schweder and Hjort 2002; Singh, Xie, and Strawderman 2005; Xie, Singh, and Strawderman 2011; Hannig and © American Statistical Association Xie 2012; Xie et al. 2013).”
A Split-and-Conquer Approach for Analysis of Extraordinarily Large Data (2014, background): “According to Singh, Xie, and Strawderman (2005), Xie, Singh, Strawderman (2011), and Liu (2012), equivalent combined statistics or asymptotic eﬃciency are achievable for many other models.”
A note on p-values interpreted as plausibilities (2012, background): “The IM framework has some connections with existing approaches, such as fiducial (Hannig 2009, 2013; Hannig and Lee 2009), confidence distributions (Xie and Singh 2013; Xie et al. 2011), Dempster–Shafer theory (Dempster 2008; Shafer 1976, 2011), generalized p-values and confidence intervals (Chiang ”
Marginal Inferential Models: Prior-Free Probabilistic Inference on Interest Parameters (2013, background): “There has been a recent effort to develop probabilistic inference without genuine priors; see, for example, generalized fiducial inference (Hannig 2009, 2013), confidence distributions (Xie and Singh 2013; Xie et al. 2011), and Bayesian inference with default, reference, or data-dependent priors (Be”