P
Peter C. Austin
Researcher at University of Toronto
Publications - 781
Citations - 75565
Peter C. Austin is an academic researcher from University of Toronto. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 112, co-authored 657 publications receiving 60156 citations. Previous affiliations of Peter C. Austin include Health Science University & Sunnybrook Research Institute.
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An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies
TL;DR: The propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects, and different causal average treatment effects and their relationship with propensity score analyses are described.
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Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples
TL;DR: Methods to determine the sampling distribution of the standardized difference when the true standardized difference is equal to zero are described, thereby allowing one to determined the range of standardized differences that are plausible with the propensity score model having been correctly specified.
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Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies
TL;DR: A suite of quantitative and qualitative methods are described that allow one to assess whether measured baseline covariates are balanced between treatment groups in the weighted sample to contribute towards an evolving concept of ‘best practice’ when using IPTW to estimate causal treatment effects using observational data.
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Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies
TL;DR: An extensive series of Monte Carlo simulations were conducted to determine the optimal caliper width for estimating differences in means (for continuous outcomes) and risk differences (for binary outcomes).
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Outcome of heart failure with preserved ejection fraction in a population-based study.
R. Sacha Bhatia,Jack V. Tu,Jack V. Tu,Douglas S. Lee,Peter C. Austin,Jiming Fang,Annick Haouzi,Yanyan Gong,Peter P. Liu,Peter P. Liu,Peter P. Liu +10 more
TL;DR: The rates of readmission for heart failure and of in-hospital complications did not differ between the two groups, and the survival of patients with heart failure with preserved ejection fraction was similar to that of Patients with reduced ejections fraction.