Cited by 812Advanced Causal Inference TechniquesStatistical Methods and Bayesian InferenceSpatial and Panel Data Analysis

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Models for Sample Selection Bias

Winship, Christopher, Mare, Robert D.·1992·Annual Review of Sociology

DOI 10.1146/annurev.so.18.080192.001551

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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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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
DOI: 10.1146/annurev.so.18.080192.001551
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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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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Models for Sample Selection Bias

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About these checks