Propensity score methods and applications / Haiyan Bai, University of Central Florida, M.H. Clark, University of Central Florida
| データ種別 | 電子書籍 |
|---|---|
| 出版者 | Los Angeles : SAGE |
| 出版年 | [2019] |
書誌詳細を非表示
| 書誌ID | OB01029268 |
|---|---|
| 本文言語 | 英語 |
| 一般注記 | Includes bibliographical references (pages 105-112) and index License restrictions may limit access Summary: "Researchers often use observational data to estimate treatment effects when randomized controlled trials or experimental designs are not feasible for social, behavioral, and health studies. Unfortunately, using observational data may threaten the internal validity of a study by introducing selection bias. To tackle this problem, Rosenbaum and Rubin (1983) introduced propensity score methods (PSM), which balances the distributions of observed covariates between treatment conditions (i.e., treatment vs. control), to reduce selection bias. Over the past three decades, PSM has become increasingly popular for making causal inferences based on observational studies. This volume provides a concise, introductory text on propensity score methods that is easy to comprehend by those who have limited background in statistics, and is practical enough for researchers to quickly generalize and apply the methods. Although there are other books on PSM, most either focus on advanced topics in PSM or on theories of PSM. This volume covers basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real world data, with exercises at the end of each chapter. Software code and datasets are available on an accompanying website"-- Provided by publisher |
| 著者標目 | *Bai, Haiyan Clark, M. H (Margaret Hilary) |
| 件 名 | LCSH:Social sciences -- Research -- Statistical methods
全ての件名で検索
LCSH:Analysis of variance |
| 分 類 | LCC:HA29 DC23:001.4/22 |
| 巻冊次 | paperback ; ISBN:9781506378053 RefWorks出力（各巻） |
| 資料種別 | 機械可読データファイル |
| 所蔵情報へのリンク | Propensity score methods and applications / Haiyan Bai, M.H. Clark ; : pbk |
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※2020年8月16日以降