Related references
Note: Only part of the references are listed.Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial
Matthew J. Smith et al.
STATISTICS IN MEDICINE (2022)
Use of copula to model within-study association in bivariate meta-analysis of binomial data at the aggregate level: A Bayesian approach and application to surrogate endpoint evaluation
Tasos Papanikos et al.
STATISTICS IN MEDICINE (2022)
Bivariate network meta-analysis for surrogate endpoint evaluation
Sylwia Bujkiewicz et al.
STATISTICS IN MEDICINE (2019)
Feasibility of Using Real-World Data to Replicate Clinical Trial Evidence
Victoria L. Bartlett et al.
JAMA NETWORK OPEN (2019)
The inclusion of real world evidence in clinical development planning
Reynaldo Martina et al.
TRIALS (2018)
Combining randomized and nonrandomized evidence in network meta-analysis
Orestis Efthimiou et al.
STATISTICS IN MEDICINE (2017)
Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available
Miguel A. Hernan et al.
AMERICAN JOURNAL OF EPIDEMIOLOGY (2016)
Combining randomized and non-randomized evidence in clinical research: a review of methods and applications
Pablo E. Verde et al.
RESEARCH SYNTHESIS METHODS (2015)
Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes
Felix A. Achana et al.
BMC MEDICAL RESEARCH METHODOLOGY (2014)
A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis
Milo A. Puhan et al.
BMJ-BRITISH MEDICAL JOURNAL (2014)
Multivariate meta-analysis of mixed outcomes: a Bayesian approach
Sylwia Bujkiewicz et al.
STATISTICS IN MEDICINE (2013)
Incorporating data from various trial designs into a mixed treatment comparison model
Susanne Schmitz et al.
STATISTICS IN MEDICINE (2013)
Non-randomized studies as a source of complementary, sequential or replacement evidence for randomized controlled trials in systematic reviews on the effects of interventions
Holger J. Schuenemann et al.
RESEARCH SYNTHESIS METHODS (2013)
Multivariate meta-analysis: the effect of ignoring within-study correlation
Richard D. Riley
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY (2009)
The binomial distribution of meta-analysis was preferred to model within-study variability
Taye H. Hamza et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2008)
Share Paper
