A Tutorial and Case Study in Propensity Score Analysis
An Application to Estimating the Effect of In-Hospital Smoking Cessation Counseling on Mortality
Bibliographic Data
| ID | 19289640 |
|---|---|
| Authors | Peter C Austin (0000-0003-3337-233X, Institute for Clinical Evaluative Sciences and University of Toronto, corresponding author) |
| Year | 2011 |
| Volume | 46 |
| Issue | 1 |
| Pages | 119-151 |
| Publication date | 2011-02-07 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Multivariate Behavioral Research (JOURNAL) |
| Journal identifiers | ISSN: 0027-3171 • E-ISSN: 1532-7906 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00273171.2011.540480 |
| PMID | 22287812 |
| PMCID | PMC3266945 |
| OpenAlex | W2065417422 |
| Language | EN |
| Citations received | 23 |
| References cited | 51 |
Propensity score methods allow investigators to estimate causal treatment effects using observational or nonrandomized data. In this article we provide a practical illustration of the appropriate steps in conducting propensity score analyses. For illustrative purposes, we use a sample of current smokers who were discharged alive after being hospitalized with a diagnosis of acute myocardial infarction. The exposure of interest was receipt of smoking cessation counseling prior to hospital discharge and the outcome was mortality with 3 years of hospital discharge. We illustrate the following concepts: first, how to specify the propensity score model; second, how to match treated and untreated participants on the propensity score; third, how to compare the similarity of baseline characteristics between treated and untreated participants after stratifying on the propensity score, in a sample matched on the propensity score, or in a sample weighted by the inverse probability of treatment; fourth, how to estimate the effect of treatment on outcomes when using propensity score matching, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, or covariate adjustment using the propensity score. Finally, we compare the results of the propensity score analyses with those obtained using conventional regression adjustment
Covariate · Inverse probability weighting · Matching (statistics) · Observational study · Propensity score matching · Statistics · Advanced Causal Inference Techniques · Health Systems, Economic Evaluations, Quality of Life · Internal Medicine · Mathematics · Medicine · Statistical Methods and Inference
The Effect of Survey Mode on Socially Undesirable Responses to Open-ended Questions
Evaluating the Health Outcomes of the Healthy Women Healthy Babies Program in Delaware
Methods for Constructing and Assessing Propensity Scores
Effectiveness of tobacco cessation pharmacotherapy in the Veterans Health Administration
Influence of chronic hepatitis C infection on the monocyte-to-platelet ratio
Protocol for a cluster-randomized clinical trial to evaluate the effectiveness of mindfulness-based cognitive therapy for depression, implemented in Vietnamese Buddhist pagoda
A comparative analysis of the impacts of digital lifestyles on the physical, mental, and social health among older internet users
Liberal Arts Graduates in the Labour Market
Assessing the Effect of School‐Based Health Centers on Achievement of National Performance Measures
The Healthy Migrant Effect’ for Mental Health in England
Do intensive specialized services prevent family separation in parents with intellectual disabilities? A treatment effects analysis
The Effect of Partnership Presence and Support on HIV Viral Suppression Among Serodiscordant Partnered and Single Heterosexual HIV-Positive Individuals in Brazil
Effects of Unconditional Cash Transfers on Asset Accumulation Among Low‐Income Households in Rural Northern Uganda
Using Ensemble-Based Methods for Directly Estimating Causal Effects
Introduction to the Special Issue on Propensity Score Methods in Behavioral Research
An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies
Are the Tickets for Everyone? Heterogeneity of Economic Rewards for Associate's Degree Completion
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Instructor use of academic alerts and its impact on student outcomes
Early-life exposure to economic stress and metabolic risks in young adulthood
Drawing Causal Inferences Using Propensity Scores
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What Does a Swiss Franc Mortgage Cost? The Tale of Polish Trust for Foreign Currency Denominated Mortgages
An Introduction to the Bootstrap
Regression Modeling Strategies
An Introduction to the Bootstrap
The Robust Inference for the Cox Proportional Hazards Model
Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome
Optimal caliper widths for propensity‐score matching when estimating differences in means and differences in proportions in observational studies
Misunderstandings Between Experimentalists and Observationalists about Causal Inference
Stratification and weighting via the propensity score in estimation of causal treatment effects
A critical appraisal of propensity‐score matching in the medical literature between 1996 and 2003
Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity‐score matched samples
Using the Standardized Difference to Compare the Prevalence of a Binary Variable Between Two Groups in Observational Research
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score
Nonparametric Estimation of Average Treatment Effects Under Exogeneity
Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference
| Unique citing works | 23 |
|---|---|
| Citations per year | 1.53 |
| Citation span | 2011 - 2026 (16) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 22 |