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Improving Semiparametric Estimation ...
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Fang, Fang.
Improving Semiparametric Estimation of Longitudinal Data with Covariance Function.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Improving Semiparametric Estimation of Longitudinal Data with Covariance Function./
作者:
Fang, Fang.
面頁冊數:
1 online resource (142 pages)
附註:
Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
Contained By:
Dissertation Abstracts International79-08B(E).
標題:
Statistics. -
電子資源:
click for full text (PQDT)
ISBN:
9780355845853
Improving Semiparametric Estimation of Longitudinal Data with Covariance Function.
Fang, Fang.
Improving Semiparametric Estimation of Longitudinal Data with Covariance Function.
- 1 online resource (142 pages)
Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
Thesis (Ph.D.)--The University of North Carolina at Charlotte, 2018.
Includes bibliographical references
In this dissertation, we aim to improve efficiency of estimation in longitudinal data under generalized semi-parametric varying-coefficient models.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355845853Subjects--Topical Terms:
556824
Statistics.
Index Terms--Genre/Form:
554714
Electronic books.
Improving Semiparametric Estimation of Longitudinal Data with Covariance Function.
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Improving Semiparametric Estimation of Longitudinal Data with Covariance Function.
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Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
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Adviser: Yanqing Sun.
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Includes bibliographical references
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In this dissertation, we aim to improve efficiency of estimation in longitudinal data under generalized semi-parametric varying-coefficient models.
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First, we investigate a profile weighted least square approach for model estimation by utilizing within subject correlations. Several methods for incorporating the within subject correlations are explored, including quasi-likelihood approach (QL), minimum generalized variance approach (MGV), the quadratic inference function approach (QIF) and newly proposed weighted least square approach (WLS). Our simulation study shows that the covariance assisted estimation is more efficient then working independence approach (WI).
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Second, we apply the above methods to more complex generalized semiparametric varying-coefficient models that not only describe time-constant effects and time-varying effects as above but also model covariate-varying effects. The asymptotic properties of the estimators are derived theoretically. The simulation study demonstrates similar results as above.
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The proposed estimation methods are applied to two real data sets. One is ACTG 244 clinical trial, the other is the STEP study with MITT cases. Both show that our methods by using correlation structure in estimation give more efficient estimation and provide more information about the data, and have broad applications in biomedical studies where within subject correlation often exists.
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click for full text (PQDT)
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