کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1149443 | 957879 | 2010 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Is regression adjustment supported by the Neyman model for causal inference?
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Is regression adjustment supported by the Neyman model for causal inference? Is regression adjustment supported by the Neyman model for causal inference?](/preview/png/1149443.png)
چکیده انگلیسی
This paper examines both theoretically and empirically whether the common practice of using OLS multivariate regression models to estimate average treatment effects (ATEs) under experimental designs is justified by the Neyman model for causal inference. Using data from eight large U.S. social policy experiments, the paper finds that estimated standard errors and significance levels for ATE estimators are similar under the OLS and Neyman models when baseline covariates are included in the models, even though theory suggests that this may not have been the case. This occurs primarily because treatment effects do not appear to vary substantially across study subjects.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 140, Issue 1, 1 January 2010, Pages 246–259
Journal: Journal of Statistical Planning and Inference - Volume 140, Issue 1, 1 January 2010, Pages 246–259
نویسندگان
Peter Z. Schochet,