The Factors Affecting Eye Patients (Cataract) In Jordan by Using the Logistic Regression Model
- Adeeb Rahamneh
- Omar Hawamdeh
Abstract
This study aims to use the logistic regression model to classify patients as infected and without cataracts. The independent variables were used to represent the gender, the age, the pressure in the right eye, the pressure in the left eye, HbA1C, and the anemia, representative variables for the study of Cataract disease affects the eyes, based on a random sample of (116) patients. The results proved that the used logistic regression model is an efficient and representative for data that shows through (Likelihood Ratio Test) and (Hosmer and Lemeshow test), and the study proved that the value of (R Square Nagelkerke=1) this means that 100% of the change in the occurred changes in the response variable explained through the Logistic regression model.
- Full Text: PDF
- DOI:10.5539/mas.v11n8p38
Journal Metrics
(The data was calculated based on Google Scholar Citations)
h5-index (July 2022): N/A
h5-median(July 2022): N/A
Index
- Aerospace Database
- American International Standards Institute (AISI)
- BASE (Bielefeld Academic Search Engine)
- CAB Abstracts
- CiteFactor
- CNKI Scholar
- Elektronische Zeitschriftenbibliothek (EZB)
- Excellence in Research for Australia (ERA)
- JournalGuide
- JournalSeek
- LOCKSS
- MIAR
- NewJour
- Norwegian Centre for Research Data (NSD)
- Open J-Gate
- Polska Bibliografia Naukowa
- ResearchGate
- SHERPA/RoMEO
- Standard Periodical Directory
- Ulrich's
- Universe Digital Library
- WorldCat
- ZbMATH
Contact
- Sunny LeeEditorial Assistant
- mas@ccsenet.org