Statistical Inference of the Class of Nonparametric Tests for the Panel Count and Current Status Data from the Perspective of the Saddlepoint Approximation

Many statisticians resort to using the asymptotic normal approximation method to carry out statistical inference for many statistical tests, especially nonparametric ones. In this article, the saddlepoint approximation method is proposed as an alternative to the asymptotic normal approximation metho...

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Main Authors: Abd El-Raheem M. Abd El-Raheem, Mona Hosny, Ehab F. Abd-Elfattah
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2023/9111653
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author Abd El-Raheem M. Abd El-Raheem
Mona Hosny
Ehab F. Abd-Elfattah
author_facet Abd El-Raheem M. Abd El-Raheem
Mona Hosny
Ehab F. Abd-Elfattah
author_sort Abd El-Raheem M. Abd El-Raheem
collection DOAJ
description Many statisticians resort to using the asymptotic normal approximation method to carry out statistical inference for many statistical tests, especially nonparametric ones. In this article, the saddlepoint approximation method is proposed as an alternative to the asymptotic normal approximation method to carry out statistical inference for a number of nonparametric tests for an important type of data that appears frequently in many clinical studies such as cancer and tumorigenicity studies. In clinical trials, there are many strategies through which treatments are assigned to patients. Equal allocation of both treatments is a largely prevalent approach in clinical trials to eliminate experimental bias and increase power. Accordingly, the statistical analysis is carried out based on the truncated binomial design, which is one of the designs that achieve a perfect balance between the two treatments. To clarify the accuracy of the proposed approximation method, two sets of real data are analyzed, and for the same purpose, a comprehensive simulation study is carried out.
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institution Kabale University
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series Journal of Mathematics
spelling doaj-art-703966dff939434f85ffccc4afdd99622025-02-03T06:04:50ZengWileyJournal of Mathematics2314-47852023-01-01202310.1155/2023/9111653Statistical Inference of the Class of Nonparametric Tests for the Panel Count and Current Status Data from the Perspective of the Saddlepoint ApproximationAbd El-Raheem M. Abd El-Raheem0Mona Hosny1Ehab F. Abd-Elfattah2Department of MathematicsDepartment of MathematicsDepartment of MathematicsMany statisticians resort to using the asymptotic normal approximation method to carry out statistical inference for many statistical tests, especially nonparametric ones. In this article, the saddlepoint approximation method is proposed as an alternative to the asymptotic normal approximation method to carry out statistical inference for a number of nonparametric tests for an important type of data that appears frequently in many clinical studies such as cancer and tumorigenicity studies. In clinical trials, there are many strategies through which treatments are assigned to patients. Equal allocation of both treatments is a largely prevalent approach in clinical trials to eliminate experimental bias and increase power. Accordingly, the statistical analysis is carried out based on the truncated binomial design, which is one of the designs that achieve a perfect balance between the two treatments. To clarify the accuracy of the proposed approximation method, two sets of real data are analyzed, and for the same purpose, a comprehensive simulation study is carried out.http://dx.doi.org/10.1155/2023/9111653
spellingShingle Abd El-Raheem M. Abd El-Raheem
Mona Hosny
Ehab F. Abd-Elfattah
Statistical Inference of the Class of Nonparametric Tests for the Panel Count and Current Status Data from the Perspective of the Saddlepoint Approximation
Journal of Mathematics
title Statistical Inference of the Class of Nonparametric Tests for the Panel Count and Current Status Data from the Perspective of the Saddlepoint Approximation
title_full Statistical Inference of the Class of Nonparametric Tests for the Panel Count and Current Status Data from the Perspective of the Saddlepoint Approximation
title_fullStr Statistical Inference of the Class of Nonparametric Tests for the Panel Count and Current Status Data from the Perspective of the Saddlepoint Approximation
title_full_unstemmed Statistical Inference of the Class of Nonparametric Tests for the Panel Count and Current Status Data from the Perspective of the Saddlepoint Approximation
title_short Statistical Inference of the Class of Nonparametric Tests for the Panel Count and Current Status Data from the Perspective of the Saddlepoint Approximation
title_sort statistical inference of the class of nonparametric tests for the panel count and current status data from the perspective of the saddlepoint approximation
url http://dx.doi.org/10.1155/2023/9111653
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