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Your search keyword '"Abdulrahman, Alanazi Talal"' showing total 24 results
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24 results on '"Abdulrahman, Alanazi Talal"'

2. Exploring Domestic Violence Causes in Saudi Arabia: Factor Analysis Approach.

Author

Alhelali, Marwan H., Alamri, Osama Abdulaziz, Abdulrahman, Alanazi Talal, Alomair, Mohammed Ahmed, and Alsaedi, Basim S. O.

Subjects
EXPLORATORY factor analysis, PRINCIPAL components analysis, DOMESTIC violence, FACTOR analysis, RESEARCH personnel
Abstract

The objective of this research is to ascertain the elements that have an impact on and drive domestic violence in Saudi Arabia, a phenomenon that has a prevalence rate of around 35% among women globally. The researchers administered a survey to a sample of 550 individuals and used exploratory factor analysis (EFA) to analyze the collected data. The findings revealed three factors: a lack of familial unity, encouragement of detrimental characteristics, and economic turmoil. The authors examined the consequences of these characteristics on preventive and intervention programs and proposed suggestions for policymakers and researchers. This research enhances the existing body of knowledge on domestic violence by conducting a statistical analysis to examine the factors that lead to it and the resulting outcomes within a particular cultural setting. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Statistical Modeling Using a New Distribution with Application in Health Data.

Author

Abdulrahman, Alanazi Talal, Alshawarbeh, Etaf, and Abd El-Raouf, Mahmoud M.

Subjects
*STATISTICAL models, *COMMUNICABLE diseases, *PARAMETER estimation, *INFECTIOUS disease transmission, *PANDEMICS
Abstract

The modeling of pandemics is significant in understanding and addressing the spread of infectious diseases. This study introduces a novel and highly flexible extension of the asymmetric unit Burr–Hatke distribution, termed the power Burr–Hatke distribution (PUBHD), and comprehensively investigates its mathematical properties. Multiple parameter estimation methods are employed, and their asymptotic behavior is analyzed through simulation experiments. The different estimation techniques are compared to identify the most efficient approach for estimating the distribution's parameters. To demonstrate the applicability and usefulness of the PUBHD model, we conducted a case study using a sample from the COVID-19 dataset and compared its performance with other established models. Our findings show that the PUBHD model provides a superior fit to the COVID-19 dataset and offers a valuable tool for accurately modeling real-life pandemics. [ABSTRACT FROM AUTHOR]

Published
2023
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