D-Index & Metrics Best Publications
Medicine
Canada
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Medicine D-index 129 Citations 76,824 869 World Ranking 1449 National Ranking 45

Research.com Recognitions

Awards & Achievements

2023 - Research.com Medicine in Canada Leader Award

2016 - Fellow of the American Statistical Association (ASA)

Overview

What is he best known for?

The fields of study he is best known for:

  • Internal medicine
  • Statistics
  • Surgery

His primary areas of investigation include Statistics, Propensity score matching, Econometrics, Observational study and Cohort study. His Propensity score matching research includes themes of Matching, Estimator, Confounding and Multivariate analysis. His work in Econometrics tackles topics such as Segmented regression which are related to areas like Proper linear model.

His studies in Observational study integrate themes in fields like Relative risk, Outcome and Pharmacoepidemiology. His Cohort study study combines topics from a wide range of disciplines, such as Demography, Surgery, Cohort and Emergency medicine. Peter C. Austin studied Covariate and Weighting that intersect with Inverse probability and Causal inference.

His most cited work include:

  • An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies (4627 citations)
  • Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples (2142 citations)
  • Outcome of heart failure with preserved ejection fraction in a population-based study. (1571 citations)

What are the main themes of his work throughout his whole career to date?

Peter C. Austin mostly deals with Internal medicine, Statistics, Retrospective cohort study, Emergency medicine and Cohort study. His biological study spans a wide range of topics, including Surgery and Cardiology. His Statistics research focuses on Econometrics and how it connects with Linear regression.

The Retrospective cohort study study which covers Confidence interval that intersects with Odds ratio. His work deals with themes such as Relative risk and Incidence, which intersect with Cohort study. Peter C. Austin has researched Propensity score matching in several fields, including Matching, Observational study, Survival analysis and Confounding.

He most often published in these fields:

  • Internal medicine (43.45%)
  • Statistics (38.98%)
  • Retrospective cohort study (26.40%)

What were the highlights of his more recent work (between 2019-2021)?

  • Internal medicine (43.45%)
  • Emergency medicine (24.95%)
  • Statistics (38.98%)

In recent papers he was focusing on the following fields of study:

Internal medicine, Emergency medicine, Statistics, Cardiology and Retrospective cohort study are his primary areas of study. The concepts of his Emergency medicine study are interwoven with issues in Psychological intervention, Health services research, Emergency department and Referral. His study in Covariate, Observational study and Propensity score matching is done as part of Statistics.

His Covariate research integrates issues from Outcome and Subdistribution hazard. His Observational study research includes themes of Matching, Confounding and Hazard ratio. The Retrospective cohort study study combines topics in areas such as Diabetes mellitus, Relative risk, Confidence interval, Guideline and Cohort.

Between 2019 and 2021, his most popular works were:

  • Transcatheter ViV Versus Redo Surgical AVR for the Management of Failed Biological Prosthesis: Early and Late Outcomes in a Propensity-Matched Cohort (32 citations)
  • Surgical valve selection in the era of transcatheter aortic valve replacement in the Society of Thoracic Surgeons Database (16 citations)
  • Surgical valve selection in the era of transcatheter aortic valve replacement in the Society of Thoracic Surgeons Database (16 citations)

In his most recent research, the most cited papers focused on:

  • Internal medicine
  • Statistics
  • Surgery

His main research concerns Internal medicine, Propensity score matching, Proportional hazards model, Statistics and Hazard ratio. His Cardiology research extends to the thematically linked field of Internal medicine. The subject of his Propensity score matching research is within the realm of Surgery.

His work carried out in the field of Proportional hazards model brings together such families of science as Econometrics, Survival function, Competing risks, Regression analysis and Subdistribution hazard. His work in the fields of Data analysis and Imputation overlaps with other areas such as Mean value, Statistical software and Statistical analyses. He interconnects Observational study, Covariate, Time-varying covariate, Event and Matching in the investigation of issues within Survival analysis.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

Peter C. Austin.
Multivariate Behavioral Research (2011)

7901 Citations

Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples

Peter C Austin.
Statistics in Medicine (2009)

3644 Citations

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.
The New England Journal of Medicine (2006)

2423 Citations

Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies

Peter C. Austin;Elizabeth A. Stuart.
Statistics in Medicine (2015)

2360 Citations

Rates of Hyperkalemia after Publication of the Randomized Aldactone Evaluation Study

David N. Juurlink;Muhammad M. Mamdani;Douglas S. Lee;Alexander Kopp.
The New England Journal of Medicine (2004)

1892 Citations

Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model.

D.S. Lee;P.C. Austin;J.L. Rouleau;P.P. Liu.
JAMA (2003)

1436 Citations

A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data.

Carl van Walraven;Peter C. Austin;Alison Jennings;Hude Quan.
Medical Care (2009)

1397 Citations

Introduction to the Analysis of Survival Data in the Presence of Competing Risks.

Peter C. Austin;Douglas S. Lee;Jason P. Fine.
Circulation (2016)

1300 Citations

A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003

Peter C. Austin.
Statistics in Medicine (2008)

1244 Citations

A population-based study of the drug interaction between proton pump inhibitors and clopidogrel

David N. Juurlink;Tara Gomes;Dennis T. Ko;Dennis T. Ko;Paul E. Szmitko.
Canadian Medical Association Journal (2009)

1237 Citations

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