Kenward‐Roger–type corrections for inference methods of network meta‐analysis and meta‐regression
出版年份 2023 全文链接
标题
Kenward‐Roger–type corrections for inference methods of network meta‐analysis and meta‐regression
作者
关键词
-
出版物
Research Synthesis Methods
Volume 14, Issue 5, Pages 731-741
出版商
Wiley
发表日期
2023-07-04
DOI
10.1002/jrsm.1652
参考文献
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- (2021) Masahiko Gosho et al. INTERNATIONAL STATISTICAL REVIEW
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- (2019) Shonosuke Sugasawa et al. BIOSTATISTICS
- Permutation Inference Methods for Multivariate Meta‐Analysis
- (2019) Hisashi Noma et al. BIOMETRICS
- Prediction intervals for random-effects meta-analysis: A confidence distribution approach
- (2018) Kengo Nagashima et al. STATISTICAL METHODS IN MEDICAL RESEARCH
- Outcomes of non-invasive diagnostic modalities for the detection of coronary artery disease: network meta-analysis of diagnostic randomised controlled trials
- (2018) George CM Siontis et al. BMJ-British Medical Journal
- Outcomes of non-invasive diagnostic modalities for the detection of coronary artery disease: network meta-analysis of diagnostic randomised controlled trials
- (2018) George CM Siontis et al. BMJ-British Medical Journal
- Methods to calculate uncertainty in the estimated overall effect size from a random-effects meta-analysis
- (2018) Areti Angeliki Veroniki et al. Research Synthesis Methods
- Bartlett-type corrections and bootstrap adjustments of likelihood-based inference methods for network meta-analysis
- (2017) Hisashi Noma et al. STATISTICS IN MEDICINE
- Random effects meta-analysis: Coverage performance of 95%confidence and prediction intervals following REML estimation
- (2016) Christopher Partlett et al. STATISTICS IN MEDICINE
- Comparison of bias-corrected covariance estimators for MMRM analysis in longitudinal data with dropouts
- (2015) Masahiko Gosho et al. STATISTICAL METHODS IN MEDICAL RESEARCH
- A design-by-treatment interaction model for network meta-analysis with random inconsistency effects
- (2014) Dan Jackson et al. STATISTICS IN MEDICINE
- Systematic Reviews of Diagnostic Test Accuracy
- (2013) Mariska M.G. Leeflang ANNALS OF INTERNAL MEDICINE
- Estimating within-study covariances in multivariate meta-analysis with multiple outcomes
- (2012) Yinghui Wei et al. STATISTICS IN MEDICINE
- Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies
- (2012) J. P. T. Higgins et al. Research Synthesis Methods
- Indirect and mixed-treatment comparison, network, or multiple-treatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool
- (2012) Georgia Salanti Research Synthesis Methods
- Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression
- (2012) Ian R. White et al. Research Synthesis Methods
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- (2010) Olivia J. Phung JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- Network Meta-Analysis with Competing Risk Outcomes
- (2010) A.E. Ades et al. VALUE IN HEALTH
- Modeling between-trial variance structure in mixed treatment comparisons
- (2009) G. Lu et al. BIOSTATISTICS
- An improved approximation to the precision of fixed effects from restricted maximum likelihood
- (2009) Michael G. Kenward et al. COMPUTATIONAL STATISTICS & DATA ANALYSIS
- A method for the meta-analysis of mutually exclusive binary outcomes
- (2008) Thomas A. Trikalinos et al. STATISTICS IN MEDICINE
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