Statistics Papers

Document Type

Journal Article

Date of this Version

8-2008

Publication Source

Evaluation Review

Volume

32

Issue

4

Start Page

392

Last Page

409

DOI

10.1177/0193841X08317586

Abstract

Regressions can be weighted by propensity scores in order to reduce bias. However, weighting is likely to increase random error in the estimates, and to bias the estimated standard errors downward, even when selection mechanisms are well understood. Moreover, in some cases, weighting will increase the bias in estimated causal parameters. If investigators have a good causal model, it seems better just to fit the model without weights. If the causal model is improperly specified, there can be significant problems in retrieving the situation by weighting, although weighting may help under some circumstances.

Keywords

causation, selection, models, experiments, observational studies, regression, propensity scores

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Date Posted: 27 November 2017

This document has been peer reviewed.