MARC보기
LDR01532nmm uu200397 4500
001000000333320
00520240805172816
008181129s2018 |||||||||||||||||c||eng d
020 ▼a 9780355930795
035 ▼a (MiAaPQ)AAI10816241
035 ▼a (MiAaPQ)wisc:15244
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 310
1001 ▼a Zhang, Ying.
24510 ▼a Efficient Treatment Effect Estimation with Dimension Reduction.
260 ▼a [S.l.] : ▼b The University of Wisconsin - Madison., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 104 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
500 ▼a Advisers: Jun Shao
5021 ▼a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2018.
520 ▼a Estimation of average and quantile treatment effects is crucial in causal inference for evaluation of treatments or interventions in biomedical, economic, and social studies. Under the assumption of treatment and potential outcomes are independe
590 ▼a School code: 0262.
650 4 ▼a Statistics.
650 4 ▼a Biostatistics.
690 ▼a 0463
690 ▼a 0308
71020 ▼a The University of Wisconsin - Madison. ▼b Statistics.
7730 ▼t Dissertation Abstracts International ▼g 79-09B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0262
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998230 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자