Drawing Causal Inferences Using Propensity Scores
A Practical Guide for Community Psychologists
Bibliographic Data
| ID | 11054982 |
|---|---|
| Authors | Stephanie T Lanza (0000-0002-6101-8381, The Methodology Center The Pennsylvania State University 204 E. Calder Way, Suite 400 16801 State College PA USA, corresponding author), Julia E Moore (0000-0002-8147-6347, Ontario Drug Policy Research Network St. Michael's Hospital G1 06, 2075 Bayview Avenue M4N 3M5 Toronto ON Canada), Nicole M Butera (0000-0002-8901-3881, The Methodology Center The Pennsylvania State University 204 E. Calder Way, Suite 400 16801 State College PA USA) |
| Year | 2013 |
| Volume | 52 |
| Issue | 3-4 |
| Pages | 380-392 |
| Publication date | 2013-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | American Journal of Community Psychology (JOURNAL) |
| Journal identifiers | ISSN: 0091-0562 • E-ISSN: 1573-2770 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1007/s10464-013-9604-4 |
| PMID | 24185755 |
| PMCID | PMC4098642 |
| OpenAlex | W2053148876 |
| Language | EN |
| Citations received | 19 |
| References cited | 34 |
Confounding present in observational data impede community psychologists’ ability to draw causal inferences. This paper describes propensity score methods as a conceptually straightforward approach to drawing causal inferences from observational data. A step‐by‐step demonstration of three propensity score methods—weighting, matching, and subclassification—is presented in the context of an empirical examination of the causal effect of preschool experiences (Head Start vs. parental care) on reading development in kindergarten. Although the unadjusted population estimate indicated that children with parental care had substantially higher reading scores than children who attended Head Start, all propensity score adjustments reduce the size of this overall causal effect by more than half. The causal effect was also defined and estimated among children who attended Head Start. Results provide no evidence for improved reading if those children had instead received parental care. We carefully define different causal effects and discuss their respective policy implications, summarize advantages and limitations of each propensity score method, and provide SAS and R syntax so that community psychologists may conduct causal inference in their own research
Causal inference · Confounding · Context (archaeology) · Developmental psychology · Matching (statistics) · Observational study · Population · Propensity score matching · Reading (process) · Advanced Causal Inference Techniques · Early Childhood Education and Development · Medicine · Psychology · School Choice and Performance
The Relationship between Veterans’ Employment Program Component Use and Career Advancement Over Time
Residential Mobility and Adolescent Achievement and Behavior
Teenaged, married, and out of school
Latent Class Analysis for Developmental Research
Examining the Causal Impact of Prenatal Home Visiting on Birth Outcomes
Propensity score weighting
Understanding influencing attributes of Covid-19 vaccine preference and willingness-to-pay among Chinese and American middle-aged and elderly adults
A Quasi-Experimental Study of the Achievement Impacts of a Replicable Summer Reading Program
Using integrated data to examine the effects of summer youth employment program completion on educational and criminal justice system outcomes
Effectiveness of the Community Prevention and Wellness Initiative
Assessing the Impact of a Media‐based Intervention to Prevent Intergroup Violence and Promote Positive Intergroup Relations in Burundi
The effects of exposure to an enhanced preschool program on the social-emotional functioning of at-risk children
One or two years of participation
HIV and Substance Use Stigma, Intersectional Stigma and Healthcare Among HIV-Positive PWID in Russia
Alcohol Use and Food Insecurity Among People Living with HIV in Mbarara, Uganda and St. Petersburg, Russia
Evaluation in the Real World
The Impact of the Project K Youth Development Program on Self-Efficacy
The Potential and Limitations of Cross-Context Comparative Research on Migration
Agroecology and household production diversity and dietary diversity
Statistical analysis with missing data
Analysis of Incomplete Multivariate Data
Missing Data
Observational Studies
Sensitivity to Exogeneity Assumptions in Program Evaluation
Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research.
Estimation of Causal Effects using Propensity Score Weighting
Variable Selection for Propensity Score Models
The Consquences of Adjustment for a Concomitant Variable That Has Been Affected by the Treatment
Average causal effects from nonrandomized studies
The importance of covariate selection in controlling for selection bias in observational studies.
Misunderstandings Between Experimentalists and Observationalists about Causal Inference
Improving propensity score weighting using machine learning
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group
Propensity Score Estimation With Boosted Regression for Evaluating Causal Effects in Observational Studies.
The central role of the propensity score in observational studies for causal effects
Matching Methods for Causal Inference
An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies
A Tutorial and Case Study in Propensity Score Analysis
Examining the link between preschool social–emotional competence and first grade academic achievement
Using full matching to estimate causal effects in nonexperimental studies
Why have Educational Evaluators Chosen Not to Do Randomized Experiments
The Dangers of Extreme Counterfactuals
| Citations per year | 1.73 |
|---|---|
| Citation span | 2015 - 2025 (11) |
| Highly cited | No |