Dr. Peter Austin is a Senior Scientist at the Institute for Clinical Evaluative Sciences (ICES) in Toronto, Canada, and a Professor in the department of Health Policy, Management and Evaluation at the University of Toronto. His research interests include statistical methods for the analysis of large health care databases, propensity-score methods for causal inference, predictive models for cardiovascular outcomes, and statistical methods for provider profiling.
Propensity score methods
Using Ensemble-Based Methods for Directly Estimating Causal Effects: An Investigation of Tree-Based G-Computation, Multivariate Behavioral Research (2012)
Researchers are increasingly using observational or nonrandomized data to estimate causal treatment effects. Essential to...
An introduction to propensity-score methods for reducing confounding in observational studies, Multivariate Behavioral Research (2011)
The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The...
A Tutorial and Case Study in Propensity Score Analysis: An Application to Estimating the Effect of In-Hospital Smoking Cessation Counseling on Mortality, Multivariate Behavioral Research (2011)
Propensity score methods allow investigators to estimate causal treatment effects using observational or nonrandomized data....
A Tutorial on Methods to Estimating Clinically and Policy-Meaningful Measures of Treatment Effects in Prospective Observational Studies: A Review (with Andreas Laupacis), The International Journal of Biostatistics (2011)
In randomized controlled trials (RCTs), treatment assignment is unconfounded with baseline covariates, allowing outcomes to...
Comparing paired vs. non-paired statistical methods of analyses when making inferences about absolute risk reductions in propensity-score matched samples., Statistics in Medicine (2011)
Propensity-score matching allows one to reduce the effects of treatment-selection bias or confounding when estimating...
Predictive models
Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a population-based cohort of subjects with schizophrenia in Ontario, Canada, Psychiatry Research (2012)
Administrative health care databases are increasingly used for health services and comparative effectiveness research. When...
Logistic regression had superior performance compared to regression trees for predicting in-hospital mortality in patients hospitalized with heart failure, Journal of Clinical Epidemiology (2010)
Objective: To compare the predictive accuracy of regression trees with that of the logistic regression...
Bootstrap model selection had similar performance for selecting authentic and noise variables compared to backwards variable elimination: a simulation study, Journal of Clinical Epidemiology. (2008)
Objective Researchers have proposed using bootstrap resampling in conjunction with automated variable selection methods to...
R and S-PLUS produced different classification trees for predicting patient mortality, Journal of Clinical Epidemiology (2008)
Objective There is a growing interest in using classification and regression trees in biomedical research....
The large-sample performance of backwards variable elimination, Journal of Applied Statistics (2008)
Prior studies have shown that automated variable selection results in models with substantially inflated estimates...
Statistical methods for provider profiling
Estimating Multilevel Logistic Regression Models When the Number of Clusters is Low: A Comparison of Different Statistical Software Procedures, The International Journal of Biostatistics (2010)
Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public...
Are (the log-odds of) Hospital Mortality Rates Normally Distributed in Ontario? Implications for Studying Variations in Outcomes of Medical Care, Journal of Evaluation in Clinical Practice (2009)
Objective: Hierarchical regression models are used to examine variations in outcomes following the provision of...
Bayes Rules for Optimally using Hierarchical Regression Models to Identify High-mortality Hospitals, BMC Health Research Methodology (2008)
Background
There is a growing trend towards the production of "hospital report-cards" in which hospitals...
Optimal Bayesian Probability Levels for Hospital Report Cards, Health Services and Outcomes Research Methodology (2008)
here is a growing trend towards the production of “hospital report-cards” in which hospitals with...
Comparing Clinical Data with Administrative Data for Producing AMI Report Cards, Journal of the Royal Statistical Society – Series A (Statistics in Society). (2006)
We compared measures of hospital performance by using both administrative and clinical data sources. Hospital-specific...
Multilevel models for health services research
Estimating Multilevel Logistic Regression Models When the Number of Clusters is Low: A Comparison of Different Statistical Software Procedures, The International Journal of Biostatistics (2010)
Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public...
Are (the log-odds of) Hospital Mortality Rates Normally Distributed in Ontario? Implications for Studying Variations in Outcomes of Medical Care, Journal of Evaluation in Clinical Practice (2009)
Objective: Hierarchical regression models are used to examine variations in outcomes following the provision of...
Bias in Penalized Quasi-Likelihood Estimation in Random Effects Logistic Regression Models when the Random Effects are not Normally Distributed, Communications in Statistics – Simulation and Computation (2005)
Regression models incorporating random effects are being used with increasing frequency to examine variations in...
Comparing hierarchical modeling with traditional logistic regression analysis among patients hospitalized with acute myocardial infarction: Should we be analyzing cardiovascular outcomes data differently?, American Heart Journal (2003)
Background: Data in health research are frequently structured hierarchically. For example, data may consist of...
An Introduction to Multilevel Regression Models, Canadian Journal of Public Health (2001)
Data in health research are frequently structured hierarchically. For example, data may consist of patients...
Randomized controlled trials
A Comparison of the Statistical Power of Different Methods for the Analysis of Repeated Cross-Sectional Cluster Randomization Trials with Binary Outcomes, The International Journal of Biostatistics (2010)
Repeated cross-sectional cluster randomization trials are cluster randomization trials in which the response variable is...
A substantial and confusing variation exists in handling of baseline covariates in randomized controlled trials: a review of trials published in leading medical journals., Journal of Clinical Epidemiology (2010)
Objective: Statisticians have criticized the use of significance testing to compare the distribution of baseline...
A comparison of the statistical power of different methods for the analysis of cluster randomization trials with binary outcomes, Statistics in Medicine (2007)
Cluster randomization trials are randomized controlled trials (RCTs) in which intact clusters of subjects are...
Impact of the Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis In Myocardial Infarction 22/Reversal of Atherosclerosis With Aggressive Lipid Lowering Trials on Trends in Intensive Versus Moderate Statin Therapy in Ontario, Canada, Circulation (2005)
Background— In March 2004, the Reversal of Atherosclerosis With Aggressive Lipid Lowering (REVERSAL) trial demonstrated...
Changes in Prescribing Patterns Following Publication of the ALLHAT Trial, Journal of the American Medical Association (2004)
Miscellaneous
The Mortality Risk Score and the ADG Score: two points-based scoring systems for the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a general adult population cohort in Ontario, Canada, Medical Care (2011)
Background: Logistic regression models that incorporated age, sex, and indicator variables for the Johns Hopkins’...
Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a general adult population cohort in Ontario, Canada, Medical Care (2011)
Background: Administrative health care databases are increasingly used for health services and comparative effectiveness research....
A data-generation process for data with specified risk differences or numbers needed to treat, Communications in Statistics - Simulation and Computation (2010)
Monte Carlo simulation methods are increasingly being used to evaluate the performance of statistical methods...
Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research, Communications in Statistics – Simulation and Computation (2009)
Researchers are increasingly using the standardized difference to compare the distribution of baseline covariates between...
Comparing clinical and administrative data for profiling hospitals on post-discharge medication use by AMI patients, American Heart Journal (2008)
Background
Postdischarge medication use is frequently used as a measure of hospital performance, with many...
Bayesian methods
Bayesian Modeling of Missing Data in Clinical Research, Computational Statistics & Data Analysis (2005)
The issue of missing data frequently confronts researchers using data derived from patient medical records....
A Comparison of Bayesian Methods for Profiling Hospital Performance, Medical Decision Making (2002)
There is a growing interest in the use of Bayesian methods for profiling institutional performance....
Bayesian Extensions of the Tobit Model for Analyzing Measures of Health Status, Medical Decision Making (2002)
Self-reported health status is often measured using utility indices that provide a score intended to...
Bayeswatch: An Overview of Bayesian Statistics, Journal of Evaluation in Clinical Practice (2002)
Increasingly, clinical research is evaluated on the quality of its statistical analysis. Traditionally, statistical analyses...
A Comparison of a Bayesian versus a Frequentist Method for Profiling Hospital Performance, Journal of Evaluation in Clinical Practice (2001)
The objective of this study was to compare the classification of hospitals as outcomes outliers...
Regression methods
Using Ensemble-Based Methods for Directly Estimating Causal Effects: An Investigation of Tree-Based G-Computation, Multivariate Behavioral Research (2012)
Researchers are increasingly using observational or nonrandomized data to estimate causal treatment effects. Essential to...
A Tutorial on Methods to Estimating Clinically and Policy-Meaningful Measures of Treatment Effects in Prospective Observational Studies: A Review (with Andreas Laupacis), The International Journal of Biostatistics (2011)
In randomized controlled trials (RCTs), treatment assignment is unconfounded with baseline covariates, allowing outcomes to...
Logistic regression had superior performance compared to regression trees for predicting in-hospital mortality in patients hospitalized with heart failure, Journal of Clinical Epidemiology (2010)
Objective: To compare the predictive accuracy of regression trees with that of the logistic regression...
Absolute risk reductions and numbers needed to treat can be obtained from adjusted survival models for time-to-event outcomes, Journal of Clinical Epidemiology (2010)
Objective: Cox proportional hazards regression models are frequently used to determine the association between exposure...
Absolute risk reductions, relative risks, relative risk reductions, and numbers needed to treat can be obtained from a logistic regression model, Journal of Clinical Epidemiology (2010)
Objective: Logistic regression models are frequently used in cohort studies to determine the association between...
Health services research
Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a population-based cohort of subjects with schizophrenia in Ontario, Canada, Psychiatry Research (2012)
Administrative health care databases are increasingly used for health services and comparative effectiveness research. When...
A Tutorial on Methods to Estimating Clinically and Policy-Meaningful Measures of Treatment Effects in Prospective Observational Studies: A Review (with Andreas Laupacis), The International Journal of Biostatistics (2011)
In randomized controlled trials (RCTs), treatment assignment is unconfounded with baseline covariates, allowing outcomes to...
Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies., Pharmaceutical Statistics (2011)
In a study comparing the effects of two treatments, the propensity score is the probability...
The Mortality Risk Score and the ADG Score: two points-based scoring systems for the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a general adult population cohort in Ontario, Canada, Medical Care (2011)
Background: Logistic regression models that incorporated age, sex, and indicator variables for the Johns Hopkins’...
Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a general adult population cohort in Ontario, Canada, Medical Care (2011)
Background: Administrative health care databases are increasingly used for health services and comparative effectiveness research....
Health related quality of life
A Comparison of Methods for Analyzing Health Related Quality of Life Measures, Value in Health (2002)
Objectives: Self-reported health status is often measured using psychometric or utility indices that provide a...
Bayesian Extensions of the Tobit Model for Analyzing Measures of Health Status, Medical Decision Making (2002)
Self-reported health status is often measured using utility indices that provide a score intended to...
Health Services Research
Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a population-based cohort of subjects with schizophrenia in Ontario, Canada, Psychiatry Research (2012)
Administrative health care databases are increasingly used for health services and comparative effectiveness research. When...
A Tutorial on Methods to Estimating Clinically and Policy-Meaningful Measures of Treatment Effects in Prospective Observational Studies: A Review (with Andreas Laupacis), The International Journal of Biostatistics (2011)
In randomized controlled trials (RCTs), treatment assignment is unconfounded with baseline covariates, allowing outcomes to...
Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies., Pharmaceutical Statistics (2011)
In a study comparing the effects of two treatments, the propensity score is the probability...
The Mortality Risk Score and the ADG Score: two points-based scoring systems for the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a general adult population cohort in Ontario, Canada, Medical Care (2011)
Background: Logistic regression models that incorporated age, sex, and indicator variables for the Johns Hopkins’...
Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a general adult population cohort in Ontario, Canada, Medical Care (2011)
Background: Administrative health care databases are increasingly used for health services and comparative effectiveness research....
Computation
Estimating Multilevel Logistic Regression Models When the Number of Clusters is Low: A Comparison of Different Statistical Software Procedures, The International Journal of Biostatistics (2010)
Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public...
General Biostatistics
Using Ensemble-Based Methods for Directly Estimating Causal Effects: An Investigation of Tree-Based G-Computation, Multivariate Behavioral Research (2012)
Researchers are increasingly using observational or nonrandomized data to estimate causal treatment effects. Essential to...
A Tutorial on Methods to Estimating Clinically and Policy-Meaningful Measures of Treatment Effects in Prospective Observational Studies: A Review (with Andreas Laupacis), The International Journal of Biostatistics (2011)
In randomized controlled trials (RCTs), treatment assignment is unconfounded with baseline covariates, allowing outcomes to...
Epidemiology
A Tutorial on Methods to Estimating Clinically and Policy-Meaningful Measures of Treatment Effects in Prospective Observational Studies: A Review (with Andreas Laupacis), The International Journal of Biostatistics (2011)
In randomized controlled trials (RCTs), treatment assignment is unconfounded with baseline covariates, allowing outcomes to...