Peter C Austin
Peter C Austin
ICES (Institute for Clinical Evaluative Sciences)
Verified email at - Homepage
Cited by
Cited by
An introduction to propensity score methods for reducing the effects of confounding in observational studies
PC Austin
Multivariate behavioral research 46 (3), 399-424, 2011
Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity‐score matched samples
PC Austin
Statistics in medicine 28 (25), 3083-3107, 2009
Outcome of heart failure with preserved ejection fraction in a population-based study
RS Bhatia, JV Tu, DS Lee, PC Austin, J Fang, A Haouzi, Y Gong, PP Liu
New England Journal of Medicine 355 (3), 260-269, 2006
Optimal caliper widths for propensity‐score matching when estimating differences in means and differences in proportions in observational studies
PC Austin
Pharmaceutical statistics 10 (2), 150-161, 2011
Rates of hyperkalemia after publication of the Randomized Aldactone Evaluation Study
DN Juurlink, MM Mamdani, DS Lee, A Kopp, PC Austin, A Laupacis, ...
New England Journal of Medicine 351 (6), 543-551, 2004
Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies
PC Austin, EA Stuart
Statistics in medicine 34 (28), 3661-3679, 2015
Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model
DS Lee, PC Austin, JL Rouleau, PP Liu, D Naimark, JV Tu
Jama 290 (19), 2581-2587, 2003
A population-based study of the drug interaction between proton pump inhibitors and clopidogrel
DN Juurlink, T Gomes, DT Ko, PE Szmitko, PC Austin, JV Tu, DA Henry, ...
Cmaj 180 (7), 713-718, 2009
A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data
C van Walraven, PC Austin, A Jennings, H Quan, AJ Forster
Medical care, 626-633, 2009
A critical appraisal of propensity‐score matching in the medical literature between 1996 and 2003
PC Austin
Statistics in medicine 27 (12), 2037-2049, 2008
A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study
PC Austin, P Grootendorst, GM Anderson
Statistics in medicine 26 (4), 734-753, 2007
Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research
PC Austin
Communications in statistics-simulation and computation 38 (6), 1228-1234, 2009
Introduction to the analysis of survival data in the presence of competing risks
PC Austin, DS Lee, JP Fine
Circulation 133 (6), 601-609, 2016
Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community
C Van Walraven, IA Dhalla, C Bell, E Etchells, IG Stiell, K Zarnke, ...
Cmaj 182 (6), 551-557, 2010
The use of propensity score methods with survival or time‐to‐event outcomes: reporting measures of effect similar to those used in randomized experiments
PC Austin
Statistics in medicine 33 (7), 1242-1258, 2014
Effects of socioeconomic status on access to invasive cardiac procedures and on mortality after acute myocardial infarction
DA Alter, CD Naylor, P Austin, JV Tu
New England Journal of Medicine 341 (18), 1359-1367, 1999
The number of subjects per variable required in linear regression analyses
PC Austin, EW Steyerberg
Journal of clinical epidemiology 68 (6), 627-636, 2015
Proportion of hospital readmissions deemed avoidable: a systematic review
C Van Walraven, C Bennett, A Jennings, PC Austin, AJ Forster
Cmaj 183 (7), E391-E402, 2011
A comparison of 12 algorithms for matching on the propensity score
PC Austin
Statistics in medicine 33 (6), 1057-1069, 2014
A comparison of propensity score methods: a case‐study estimating the effectiveness of post‐AMI statin use
PC Austin, MM Mamdani
Statistics in medicine 25 (12), 2084-2106, 2006
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