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Missing Data in Meta-Analysis.
~
Chowdhry, Amit Kumar.
Missing Data in Meta-Analysis.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Missing Data in Meta-Analysis./
作者:
Chowdhry, Amit Kumar.
面頁冊數:
1 online resource (162 pages)
附註:
Source: Dissertation Abstracts International, Volume: 77-08(E), Section: B.
標題:
Statistics. -
電子資源:
click for full text (PQDT)
ISBN:
9781339549446
Missing Data in Meta-Analysis.
Chowdhry, Amit Kumar.
Missing Data in Meta-Analysis.
- 1 online resource (162 pages)
Source: Dissertation Abstracts International, Volume: 77-08(E), Section: B.
Thesis (Ph.D.)--University of Rochester, 2016.
Includes bibliographical references
Missing data is a problem seen throughout applied statistical analysis. Meta-analysis has many important applications throughout a wide variety of areas of research, including medicine, epidemiology, and the social sciences. Our review of the literature suggests that there exists a wide gap between state-of-the-art methods to accommodate missing data and current practice in meta-analysis. The widely used methodology in meta-analysis is only valid under very strict assumptions, and even then not necessarily as powerful as principled methods. This dissertation proposes multiple-imputation-based methods to handle missing sample variances, missing correlations from cross-over studies, and missing covariates in meta-regression. Our work has shown that the use of principled missing data methods will improve the practice of meta-analysis in the setting of missing data.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781339549446Subjects--Topical Terms:
556824
Statistics.
Index Terms--Genre/Form:
554714
Electronic books.
Missing Data in Meta-Analysis.
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