Literature DB >> 26461816

Rejoinder to the discussion of "a Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons," by S. Dias and A. E. Ades.

Hwanhee Hong1, Haitao Chu2, Jing Zhang3, Bradley P Carlin2.   

Abstract

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Year:  2015        PMID： 26461816      PMCID： PMC4779393          DOI： 10.1002/jrsm.1186

Source DB:  PubMed          Journal:  Res Synth Methods        ISSN： 1759-2879            Impact factor:   5.273


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  4 in total

1.  Incorporation of individual-patient data in network meta-analysis for multiple continuous endpoints, with application to diabetes treatment.

Authors:  Hwanhee Hong; Haoda Fu; Karen L Price; Bradley P Carlin
Journal:  Stat Med       Date:  2015-04-30       Impact factor: 2.373

2.  Meta-analysis of safety for low event-rate binomial trials.

Authors:  Jonathan J Shuster; Jennifer D Guo; Jay S Skyler
Journal:  Res Synth Methods       Date:  2012-03       Impact factor: 5.273

3.  Bivariate random effects models for meta-analysis of comparative studies with binary outcomes: methods for the absolute risk difference and relative risk.

Authors:  Haitao Chu; Lei Nie; Yong Chen; Yi Huang; Wei Sun
Journal:  Stat Methods Med Res       Date:  2010-12-21       Impact factor: 3.021

4.  Bayesian hierarchical models for network meta-analysis incorporating nonignorable missingness.

Authors:  Jing Zhang; Haitao Chu; Hwanhee Hong; Beth A Virnig; Bradley P Carlin
Journal:  Stat Methods Med Res       Date:  2015-07-28       Impact factor: 3.021
  4 in total
  20 in total

1.  A Bayesian hierarchical model for network meta-analysis of multiple diagnostic tests.

Authors:  Xiaoye Ma; Qinshu Lian; Haitao Chu; Joseph G Ibrahim; Yong Chen
Journal:  Biostatistics       Date:  2018-01-01       Impact factor: 5.899

2.  Quantifying and presenting overall evidence in network meta-analysis.

Authors:  Lifeng Lin
Journal:  Stat Med       Date:  2018-07-18       Impact factor: 2.373

3.  The impact of covariance priors on arm-based Bayesian network meta-analyses with binary outcomes.

Authors:  Zhenxun Wang; Lifeng Lin; James S Hodges; Haitao Chu
Journal:  Stat Med       Date:  2020-06-03       Impact factor: 2.373

4.  Bayesian hierarchical methods for meta-analysis combining randomized-controlled and single-arm studies.

Authors:  Jing Zhang; Chia-Wen Ko; Lei Nie; Yong Chen; Ram Tiwari
Journal:  Stat Methods Med Res       Date:  2018-02-13       Impact factor: 3.021

5.  A Bayesian approach to discrete multiple outcome network meta-analysis.

Authors:  Rebecca Graziani; Sergio Venturini
Journal:  PLoS One       Date:  2020-04-28       Impact factor: 3.240

6.  BRIDGING RANDOMIZED CONTROLLED TRIALS AND SINGLE-ARM TRIALS USING COMMENSURATE PRIORS IN ARM-BASED NETWORK META-ANALYSIS.

Authors:  Zhenxun Wang; Lifeng Lin; Thomas Murray; James S Hodges; Haitao Chu
Journal:  Ann Appl Stat       Date:  2021-12-21       Impact factor: 1.959

7.  A variance shrinkage method improves arm-based Bayesian network meta-analysis.

Authors:  Zhenxun Wang; Lifeng Lin; James S Hodges; Richard MacLehose; Haitao Chu
Journal:  Stat Methods Med Res       Date:  2020-08-05       Impact factor: 3.021

8.  Performing Arm-Based Network Meta-Analysis in R with the pcnetmeta Package.

Authors:  Lifeng Lin; Jing Zhang; James S Hodges; Haitao Chu
Journal:  J Stat Softw       Date:  2017-08-29       Impact factor: 6.440

9.  Sensitivity to Excluding Treatments in Network Meta-analysis.

Authors:  Lifeng Lin; Haitao Chu; James S Hodges
Journal:  Epidemiology       Date:  2016-07       Impact factor: 4.822

10.  Bayesian meta-analysis using SAS PROC BGLIMM.

Authors:  Kollin W Rott; Lifeng Lin; James S Hodges; Lianne Siegel; Amy Shi; Yong Chen; Haitao Chu
Journal:  Res Synth Methods       Date:  2021-07-21       Impact factor: 5.273
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