New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare

Control chart is as a highly reputable statistical quality control tool in monitoring process stability. The classical control charts are designed on the basis of normality assumption, which is often not valid for real situations in industry; such violation of normality render the charts less accura...

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Main Authors: Atta, A.M.A., Syed Yahaya, Sharipah Soaad, Zain, Zakiyah, Ahmad, Nurzalikha
Format: Article
Language:English
Published: Advanced Scientific Research 2020
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Online Access:http://repo.uum.edu.my/27547/1/SRP%202020%2011%204%20217%20222.pdf
http://repo.uum.edu.my/27547/
http://doi.org/10.31838/srp.2020.4.31
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spelling my.uum.repo.275472020-10-01T02:45:01Z http://repo.uum.edu.my/27547/ New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare Atta, A.M.A. Syed Yahaya, Sharipah Soaad Zain, Zakiyah Ahmad, Nurzalikha QA75 Electronic computers. Computer science Control chart is as a highly reputable statistical quality control tool in monitoring process stability. The classical control charts are designed on the basis of normality assumption, which is often not valid for real situations in industry; such violation of normality render the charts less accurate. This paper presents an alternative skewness correction S (SC-S) chart specifically developed to monitor process dispersion (e.g.S for standard deviation) for skewed distributions. Its false alarm rate (Type I error) is compared with those of various heuristics charts and standard S chart, while the probability of out-of-control (OOC) detection is evaluated along with the exact S chart. The proposed charts designed for process variables following Weibull and gamma distributions are assessed alongside the normal distribution. An extensive simulation study affirms that the SC-S chart performs well in regard to false alarm rate at wide range of skewness levels and sample sizes. Meanwhile, its probability of OOC detection is closer to that of the exact S chart in comparison to the established charts. In conclusion, the new SC-S chart outperforms the established ones in monitoring process dispersion for skewed distributions. Advanced Scientific Research 2020 Article PeerReviewed application/pdf en http://repo.uum.edu.my/27547/1/SRP%202020%2011%204%20217%20222.pdf Atta, A.M.A. and Syed Yahaya, Sharipah Soaad and Zain, Zakiyah and Ahmad, Nurzalikha (2020) New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare. Systematic Reviews in Pharmacy, 11 (04). pp. 217-222. ISSN 09762779 http://doi.org/10.31838/srp.2020.4.31 doi:10.31838/srp.2020.4.31
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutional Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Atta, A.M.A.
Syed Yahaya, Sharipah Soaad
Zain, Zakiyah
Ahmad, Nurzalikha
New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare
description Control chart is as a highly reputable statistical quality control tool in monitoring process stability. The classical control charts are designed on the basis of normality assumption, which is often not valid for real situations in industry; such violation of normality render the charts less accurate. This paper presents an alternative skewness correction S (SC-S) chart specifically developed to monitor process dispersion (e.g.S for standard deviation) for skewed distributions. Its false alarm rate (Type I error) is compared with those of various heuristics charts and standard S chart, while the probability of out-of-control (OOC) detection is evaluated along with the exact S chart. The proposed charts designed for process variables following Weibull and gamma distributions are assessed alongside the normal distribution. An extensive simulation study affirms that the SC-S chart performs well in regard to false alarm rate at wide range of skewness levels and sample sizes. Meanwhile, its probability of OOC detection is closer to that of the exact S chart in comparison to the established charts. In conclusion, the new SC-S chart outperforms the established ones in monitoring process dispersion for skewed distributions.
format Article
author Atta, A.M.A.
Syed Yahaya, Sharipah Soaad
Zain, Zakiyah
Ahmad, Nurzalikha
author_facet Atta, A.M.A.
Syed Yahaya, Sharipah Soaad
Zain, Zakiyah
Ahmad, Nurzalikha
author_sort Atta, A.M.A.
title New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare
title_short New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare
title_full New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare
title_fullStr New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare
title_full_unstemmed New skewness correction S control chart for monitoring dispersion of skewed data with application in healthcare
title_sort new skewness correction s control chart for monitoring dispersion of skewed data with application in healthcare
publisher Advanced Scientific Research
publishDate 2020
url http://repo.uum.edu.my/27547/1/SRP%202020%2011%204%20217%20222.pdf
http://repo.uum.edu.my/27547/
http://doi.org/10.31838/srp.2020.4.31
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score 13.159267