Estimation of Causal Effect and Adjustment of Survey Data using Propensity Scores

DOI 4 Citations 49 References
  • HOSHINO Takahiro
    Department of Interdisciplinary Statistics, The Institute of Statistical Mathematics
  • SHIGEMASU Kazuo
    Department of Cognitive and Behavioral Science, University of Tokyo

Bibliographic Information

Other Title
  • 傾向スコア解析法による因果効果の推定と調査データの調整について

Abstract

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.

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Details 詳細情報について

  • CRID
    1390001205178467072
  • NII Article ID
    130004477280
  • DOI
    10.2333/jbhmk.31.43
  • ISSN
    18804705
    03855481
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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