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Methods for Improving Efficiency of Planned Missing Data Designs
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Methods for Improving Efficiency of Planned Missing Data Designs. |
| 개인저자 | Imbriano, Paul M. |
| 단체저자명 | University of Michigan. Biostatistics. |
| 발행사항 | [S.l.]: University of Michigan., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 111 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438126589 |
| 학위논문주기 | Thesis (Ph.D.)--University of Michigan, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Trivellore E. Raghunathan. |
| 요약 | Any survey specifically constructed so that at least some variables are unobserved on a subset of participants is a planned missing data design, where missing data represent an intentional feature of the study. Use of planned missing data design |
| 요약 | First, we propose new methods for selecting our second phase sample in two-phase surveys to reduce the variance of our estimate. When our outcome variable is continuous, we can use the data collected in Phase I for selecting our Phase II sample |
| 요약 | Next, we examine the performance of several design allocations for implementing a split questionnaire survey in a longitudinal study. While many papers examined the administration of split questionnaire designs in cross-sectional studies, resear |
| 요약 | Finally, we propose a method for improving variable allocation in split questionnaire designs. We establish a criterion that allows us to determine which variable allocations minimize the loss of information due to missing data. We use the Kullb |
| 일반주제명 | Biostatistics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
