書誌事項
- タイトル別名
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- Estimation of Causal Effect and Adjustment of Survey Data using Propensity Scores
抄録
In behavioral sciences, it is often difficult to execute an experimental study with random assignment. Therefore researchers usually do a quasi-experiment or a survey study without random assignment.<br>However, under these studies the distributions of the covariates that would affect dependent variables usually differ with the values of the independent variables.<br>To eliminate the influence of the covariates, various adjustment methods such as analysis of covariance have been applied to these data.<br>Recently new adjustment methods using the propensity score proposed by Rosenbaum & Rubin (1983) have been applied to many researches especially in the areas of medicine or economics, and these methods also attract attention in behavioral sciences.<br>The propensity score methods are also used for adjustment of survey data.<br>In this paper, we give a detailed explanation of several estimation methods of causal effect using the propensity scores and related topics.<br>We also review adjustment methods of biased survey data using the propensity scores.
収録刊行物
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- 行動計量学
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行動計量学 31 (1), 43-61, 2004
日本行動計量学会
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詳細情報 詳細情報について
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- CRID
- 1390001205178467072
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- NII論文ID
- 130004477280
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- ISSN
- 18804705
- 03855481
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可