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Likelihood-based Inferential Methods...

Xue, Yuqing .

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Likelihood-based Inferential Methods Testing Effect Size Measures for Stratified Correlated Binary Data with Bilateral Outcomes.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Likelihood-based Inferential Methods Testing Effect Size Measures for Stratified Correlated Binary Data with Bilateral Outcomes./
作者:	Xue, Yuqing .
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	146 p.
附註:	Source: Dissertations Abstracts International, Volume: 81-09, Section: B.
Contained By:	Dissertations Abstracts International81-09B.
標題:	Biostatistics. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27736641
ISBN:	9781658421201

Likelihood-based Inferential Methods Testing Effect Size Measures for Stratified Correlated Binary Data with Bilateral Outcomes.
Xue, Yuqing .

Likelihood-based Inferential Methods Testing Effect Size Measures for Stratified Correlated Binary Data with Bilateral Outcomes. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 146 p.

Source: Dissertations Abstracts International, Volume: 81-09, Section: B.

Thesis (Ph.D.)--State University of New York at Buffalo, 2020.

This item must not be sold to any third party vendors.

Binary data with bilateral outcomes is often encountered in medical comparative clinical studies where patients receive treatment on paired organs or body parts. Usually, one would expect the measurement contributed from the paired organs of the single person to be correlated. Methods of analysis that overlooked this feature of intraclass correlation may lead to an invalid inference. Taking this issue into consideration, we developed a series of likelihood-based test statistics for proportion-related effect measures on stratified correlated binary data with bilateral outcomes, including (1) three homogeneity test statistics for proportion ratios across strata based on Likelihood ratio test, Score test, and Wald-type test, (2) four confidence interval estimators (unconstrained and semi-constrained MLE-based weighted Wald-type confidence interval, profile likelihood confidence interval, and constrained MLE-based Score confidence interval) for proportion ratios, and (3) three test statistics testing the homogeneity of odds ratios. Two types of Monte Carlo simulation studies were designed and conducted to evaluate the performance of the proposed testing methods and confidence interval estimators. The presented testing procedures were demonstrated by revisiting the illustrative rheumatology study.

ISBN: 9781658421201Subjects--Topical Terms:

1002712
Biostatistics.
Subjects--Index Terms:

Bilateral outcomes

Likelihood-based Inferential Methods Testing Effect Size Measures for Stratified Correlated Binary Data with Bilateral Outcomes.
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500 $a Source: Dissertations Abstracts International, Volume: 81-09, Section: B.
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506 $a This item must not be sold to any third party vendors.
506 $a This item must not be sold to any third party vendors.
520 $a Binary data with bilateral outcomes is often encountered in medical comparative clinical studies where patients receive treatment on paired organs or body parts. Usually, one would expect the measurement contributed from the paired organs of the single person to be correlated. Methods of analysis that overlooked this feature of intraclass correlation may lead to an invalid inference. Taking this issue into consideration, we developed a series of likelihood-based test statistics for proportion-related effect measures on stratified correlated binary data with bilateral outcomes, including (1) three homogeneity test statistics for proportion ratios across strata based on Likelihood ratio test, Score test, and Wald-type test, (2) four confidence interval estimators (unconstrained and semi-constrained MLE-based weighted Wald-type confidence interval, profile likelihood confidence interval, and constrained MLE-based Score confidence interval) for proportion ratios, and (3) three test statistics testing the homogeneity of odds ratios. Two types of Monte Carlo simulation studies were designed and conducted to evaluate the performance of the proposed testing methods and confidence interval estimators. The presented testing procedures were demonstrated by revisiting the illustrative rheumatology study.
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653 $a Correlated binary data
653 $a Stratified design
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