COVARIATE SELECTION FOR PROPENSITY SCORE MODELS IN IPW ESTIMATING QUANTILE TREATMENT EFFECTS

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Other Title
  • 傾向スコアを用いた分位点処置効果のIPW推定法における共変量選択について

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Description

  Covariates for inclusion in the propensity score model is an important issue. The performances of the estimator are improved in the estimation of the average treatment effect by including covariates related to outcome in the propensity score model. However, discussions on the covariates that should be included in the propensity score model when estimating quantile treatment effects are limited. This study examines the performances of the estimators of quantile treatment effects depending on the covariates included in the propensity score model through numerical experiments. Under several scenarios, we evaluate the performances (standard deviation, relative bias, relative RMSE) of the estimation methods by specifying the covariates related to outcome. The results confirm that the methodology for the selection of covariates performs better in a heterogeneous error variance of the outcome regression model. Furthermore, we confirm covariates that affect the variance and not the value, perform better when included in the propensity score model.

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Details 詳細情報について

  • CRID
    1390019977295371904
  • DOI
    10.20551/jscswabun.37.1_3
  • ISSN
    21899789
    09148930
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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