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Statistical modeling via bootstrapping and weighted techniques based on variances

Wan Ahmad, Wan Muhamad Amir and Aleng, Nor Azlida and Ali, Z and Mohd Ibrahim, Mohamad Shafiq (2018) Statistical modeling via bootstrapping and weighted techniques based on variances. Engineering, Technology & Applied Science Research, 8 (4). pp. 3135-3140. ISSN 2241-4487 E-ISSN 1792-8036

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Multiple logistic regression is a methodology of handling dependent variables with a binary outcome. This method is becoming increasingly widespread as a statistical technique that represents a discrete probability model. Many studies have focused on the application but less on the methodology building. This study aims to provide an applied method for multiple logistic regression which is called modified Bayesian logistic regression modeling as an alternative technique for logistic regression analysis that focuses on a combination of the bootstrap method using SAS macro and weighted techniques based on variances using SAS algorithm. Data on oral cancer were applied to illustrate a real scenario of oral health data. This data will be applied to the multiple logistic regression algorithm and modified Bayesian logistic regression. Results from both cases are strongly supported by clinical studies. Through the proposed algorithm, the researcher will have an option whether to analyze the data with the usual or an alternative method. Final results indicate that the modified procedure can provide more efficient results especially for the case which involves statistical inferences.

Item Type: Article (Journal)
Additional Information: 8915/72207
Uncontrolled Keywords: multiple logistic regression; bootstrap; Bayesian and weighted techniques
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA276 Mathematical Statistics
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Dentistry
Kulliyyah of Dentistry > Department of Paediatric Dentistry and Dental Public Health
Depositing User: Dr Mohamad Shafiq Mohd Ibrahim
Date Deposited: 16 May 2019 13:47
Last Modified: 16 May 2019 13:48
URI: http://irep.iium.edu.my/id/eprint/72207

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