مقالة

The Discriminate Analysis with Applied on Diabetes non- Diabetes in Sana’a, Yemen for the Year 2025

 This study aimed to identify the most significant factors distinguishing between diabetes and non-diabetes, using linear discriminant analysis LDA. A sample of 368 individuals (225 diabetes mellitus, 143 non- diabetes mellitus) was analyzed based on data collected through via personal interviews and Al-Thawrah General Hospital in the capital Sana’a records, for the year 2025. The stepwise discriminant analysis led to the building of a statistically significant model. Results revealed that the variables (x5) body mass index BMI, (x10) Cholesterol, ( x6) Gout, (x9) Blood pressure, and ( x2) Age, had the highest discriminative power, as indicated by standardized coefficients and Wilks’ Lambda values (p < 0.05). These variables significantly contributed to classifying cases, while the remaining variables did not demonstrate a significant effect. The overall correct classification rate for diabetes mellitus DM reached 87.3%, when the overall classification accuracy of the model reached 89.9%, confirming its strong predictive power.

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Amtalteef M.A. Al-Hamzi
Department of Mathematical, Faculty of Education, Sana’a University, Sana’a, Yemen
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Amani M.A. Al-Hamzi
Department of Pediatric, Faculty of Medicine, Sana’a University, Sana’a, Yemen.
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The Discriminate Analysis with Applied on Diabetes non- Diabetes in Sana’a, Yemen for the Year 2025. (2026). مجلة جامعة صنعاء للعلوم التطبيقية والتكنولوجيا, 4(4), 1967-1976. https://doi.org/10.59628/jast.v4i4.2555

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