Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls
2009 · BMJ · 6,841 citations
https://doi.org/10.1136/bmj.b2393
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John B. Carlin
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John B. Carlin is an academic researcher from The University of Melbourne. The author has contributed to research in topics: Statistical Methods and Bayesian Inference & Advanced Causal Inference Techniques & Neonatal Respiratory Health Research. The author has an h-index of 115, co-authored 685 publications.
ORCID: 0000-0002-2694-9463Papers by this author
worksStatistical tests, P values, confidence intervals, and power: a guide to misinterpretations
2016 · European Journal of Epidemiology · 3,048 citations
https://doi.org/10.1007/s10654-016-0149-3
Beyond Power Calculations
2014 · Perspectives on Psychological Science · 1,283 citations
https://doi.org/10.1177/1745691614551642
The Epidemiology of Childhood Cardiomyopathy in Australia
2003 · New England Journal of Medicine · 766 citations
https://doi.org/10.1056/nejmoa021737
Bias and efficiency of multiple imputation compared with complete‐case analysis for missing covariate values
2010 · Statistics in Medicine · 734 citations
https://doi.org/10.1002/sim.3944
Regression models for twin studies: a critical review
2005 · International Journal of Epidemiology · 482 citations
https://doi.org/10.1093/ije/dyi153
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