Search Results - "Austin, Peter"

The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments by Austin, Peter C.

“…Propensity score methods are increasingly being used to estimate causal treatment effects in observational studies. In medical and epidemiological studies,…”
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Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis by Austin, Peter C.

“…Propensity score methods are used to reduce the effects of observed confounding when using observational data to estimate the effects of treatments or…”
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A comparison of 12 algorithms for matching on the propensity score by Austin, Peter C.

“…Propensity‐score matching is increasingly being used to reduce the confounding that can occur in observational studies examining the effects of treatments or…”
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The performance of different propensity score methods for estimating marginal hazard ratios by Austin, Peter C.

“…Propensity score methods are increasingly being used to reduce or minimize the effects of confounding when estimating the effects of treatments, exposures, or…”
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A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications by Austin, Peter C.

“…Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health,…”
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Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples by Austin, Peter C.

“…The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated…”
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An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies by Austin, Peter C.

“…The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and…”
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Intermediate and advanced topics in multilevel logistic regression analysis by Austin, Peter C., Merlo, Juan

“…Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common…”
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A Tutorial and Case Study in Propensity Score Analysis: An Application to Estimating the Effect of In-Hospital Smoking Cessation Counseling on Mortality by Austin, Peter C.

“…Propensity score methods allow investigators to estimate causal treatment effects using observational or nonrandomized data. In this article we provide a…”
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Statistical Criteria for Selecting the Optimal Number of Untreated Subjects Matched to Each Treated Subject When Using Many-to-One Matching on the Propensity Score by AUSTIN, Peter C

“…Propensity-score matching is increasingly being used to estimate the effects of treatments using observational data. In many-to-one (M:1) matching on the…”
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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 by Austin, Peter C., Stuart, Elizabeth A.

“…The propensity score is defined as a subject's probability of treatment selection, conditional on observed baseline covariates. Weighting subjects by the…”
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A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003 by Austin, Peter C.

“…Propensity‐score methods are increasingly being used to reduce the impact of treatment‐selection bias in the estimation of treatment effects using…”
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Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies by Austin, Peter C.

“…In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured…”
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Practical recommendations for reporting Fine‐Gray model analyses for competing risk data by Austin, Peter C., Fine, Jason P.

“…In survival analysis, a competing risk is an event whose occurrence precludes the occurrence of the primary event of interest. Outcomes in medical research are…”
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Introduction to the Analysis of Survival Data in the Presence of Competing Risks by Austin, Peter C, Lee, Douglas S, Fine, Jason P

“…Competing risks occur frequently in the analysis of survival data. A competing risk is an event whose occurrence precludes the occurrence of the primary event…”
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Bootstrap vs asymptotic variance estimation when using propensity score weighting with continuous and binary outcomes by Austin, Peter C.

“…We used Monte Carlo simulations to compare the performance of asymptotic variance estimators to that of the bootstrap when estimating standard errors of…”
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A review of the use of time‐varying covariates in the Fine‐Gray subdistribution hazard competing risk regression model by Austin, Peter C., Latouche, Aurélien, Fine, Jason P.

“…In survival analysis, time‐varying covariates are covariates whose value can change during follow‐up. Outcomes in medical research are frequently subject to…”
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Comparing paired vs non-paired statistical methods of analyses when making inferences about absolute risk reductions in propensity-score matched samples by Austin, Peter C.

“…Propensity‐score matching allows one to reduce the effects of treatment‐selection bias or confounding when estimating the effects of treatments when using…”
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Assessing covariate balance when using the generalized propensity score with quantitative or continuous exposures by Austin, Peter C

“…Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score…”
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Assessing the performance of the generalized propensity score for estimating the effect of quantitative or continuous exposures on binary outcomes by Austin, Peter C.

“…Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score…”
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