Models for Sample Selection Bias
Abstract
When observations in social research are selected so that they are not independent of the outcome variables in a study, sample selection leads to biased inferences about social processes. Nonrandom selection is both a source of bias in empirical research and a fundamental aspect of many social processes. This chapter reviews models that attempt to take account of sample selection and their applications in research on labor markets, schooling, legal processes, social mobility, and social networks. Variants of these models apply to outcome variables that are censored or truncated—whether explicitly or incidentally—and include the tobit model, the standard selection model, models for treatment effects in quasi-experimental designs, and endogenous switching models. Heckman’s two-stage estimator is the most widely used approach to selection bias, but its results may be sensitive to violations of its assumptions about the way that selection occurs. Recent econometric research has developed a wide variety of promising approaches to selection bias that rely on considerably weaker assumptions. These include a number of semiand nonparametric approaches to estimating selection models, the use of panel data, and the analyses of bounds of estimates. The large number of available methods and the difficulty of modelling selection indicate that researchers should be explicit about the assumptions behind their methods and should present results that derive from a variety of methods.
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Sample selection bias occurs when sample membership is not independent of the outcome.
“Sample selection bias occurs when the selection of observations into a sample is not independent of the outcome”
From Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable (2014) · cites this paper as Winship & Mare 1992
Sociological surveys of sample selection bias tend to focus on cases where selection is affected by treatment or outcome, i.e., after treatment.
“Surveys of sample selection bias in sociology tend to emphasize examples where selection is affected by the treatment or the outcome, i.e., where sample selection occurs after treatment”
From Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable (2014) · cites this paper as Winship & Mare 1992
The sampling strategy may have introduced selection bias: recruitment through advocacy organizations may capture more resource-aware researchers than those struggling in isolation.
“Our sampling strategy may have introduced selection bias [78]: recruitment through advocacy organizations may capture more resource-aware researchers than those struggling in isolation.”
From "I Don't Trust Any Professional Research Tool": A Re-Imagination of Knowledge Production Workflows by, with, and for Blind and Low-Vision Researchers (2026) · cites this paper as [78]
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- Authors
- Winship, C., & Mare, R. D.
- Affiliations
- Northwestern University (US)
- University of Wisconsin–Madison (US)
- ORCID
- Winship, Christopher
- Venue
- Annual Review of Sociology
- Publisher
- Annual Reviews
- Published
- 1992-08
- Volume
- 18
- Issue
- 1
- Pages
- 327-350
- ISSN
- 0360-0572 (ISSN-L)
- 1545-2115
- OpenAlex
- W2011111286
- Cited by
- 812
- References
- 80
- Citations by year
- 2026: 19 · 2025: 17 · 2024: 38 · 2023: 35 · 2022: 39 · 2021: 18 · 2020: 28 · 2019: 15 · 2018: 30 · 2017: 30 · 2016: 34 · 2015: 30 · 2014: 42 · 2013: 42 · 2012: 32
- FWCI
- 8.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Sociology (publishedVersion)
- Funders
- National Science Foundation
- National Institutes of Health
- National Institute of Child Health and Human Development
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Keywords
- sample selection bias, selection model, Tobit model, endogenous switching regression, panel data, treatment effect bounds, labor market, school education, legal procedure, social mobility, social networks
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