LDR | | 02294nmm uu200409 4500 |
001 | | 000000333021 |
005 | | 20240805172034 |
008 | | 181129s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438154216 |
035 | |
▼a (MiAaPQ)AAI10790998 |
035 | |
▼a (MiAaPQ)umd:18928 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
082 | 0 |
▼a 310 |
100 | 1 |
▼a Mercer, Andrew William. |
245 | 10 |
▼a Selection Bias in Nonprobability Surveys: A Causal Inference Approach. |
260 | |
▼a [S.l.] :
▼b University of Maryland, College Park.,
▼c 2018 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
300 | |
▼a 153 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
500 | |
▼a Adviser: Frauke Kreuter. |
502 | 1 |
▼a Thesis (Ph.D.)--University of Maryland, College Park, 2018. |
520 | |
▼a Many in the survey research community have expressed concern at the growing popularity of nonprobability surveys. The absence of random selection prompts justified concerns about self-selection producing biased results and means that traditional |
520 | |
▼a This dissertation proposes an alternative classification for sources of selection bias for nonprobability surveys based on principles borrowed from the field of causal inference. The proposed typology describes selection bias in terms of the thr |
520 | |
▼a Next, we show how net selection bias can be decomposed into separate additive components associated with exchangeability, positivity, and composition respectively. Using 10 parallel nonprobability surveys from different sources, we estimate thes |
520 | |
▼a Finally, using the same six measures of civic engagement, we compare the performance of four approaches to nonprobability estimation based on Bayesian additive regression trees. These are propensity weighting (PW), outcome regression (OR), and t |
590 | |
▼a School code: 0117. |
650 | 4 |
▼a Statistics. |
690 | |
▼a 0463 |
710 | 20 |
▼a University of Maryland, College Park.
▼b Survey Methodology. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0117 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997618
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자 |