Diagnose Insomnia by using Fuzzy Multiple Ordinal Logistic  Regression

Authors

  • Bashar Khalid Ali Department of Statistics, Administration and Economics College, Kerbala University- Kerbala –Iraq Author
  • Sackineh Shamil Jasim Department of Statistics, Administration and Economics College, Kerbala University- Kerbala –Iraq Author

DOI:

https://doi.org/10.62933/azx8wg44

Keywords:

Insomnia Crisp set Fuzzy set Granular fuzzy set Ordinal logistic regression

Abstract

This research utilized a questionnaire designed to diagnose and analyze insomnia using the ordinal logistic regression model. The model was applied to traditional, fuzzy, and granular fuzzy data. Two hundred questionnaires were distributed across five locations, or "granules": the College of Nursing (40 questionnaires), the College of Administration and Economics (45 questionnaires), the College of Science (40 questionnaires), the College of Education (35 questionnaires), and the Middle Euphrates Department (35 questionnaires). The target audience included professors, staff, and male and female students from various age groups. The study concluded that the ordinal logistic regression model for a granular fuzzy sample was more accurate than using traditional and fuzzy data. Analysis of the phenomenon of insomnia revealed that it has physical and psychological effects, manifesting as fatigue, headaches, and poor concentration due to unhealthy habits such as excessive caffeine consumption, irregular sleep patterns, and excessive use of electronic devices

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Published

2026-04-03

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Section

Original Articles

How to Cite

Diagnose Insomnia by using Fuzzy Multiple Ordinal Logistic  Regression. (2026). Iraqi Statisticians Journal, 3(1), 202-231. https://doi.org/10.62933/azx8wg44