Open Access Library Journal

Volume 11, Issue 8 (August 2024)

ISSN Print: 2333-9705   ISSN Online: 2333-9721

Google-based Impact Factor: 1.18  Citations  

Estimating the Likelihood of Cancer Occurrence Based on Patient Data and Lifestyle Factors: A Comparison between Logit and Probit Regression

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DOI: 10.4236/oalib.1111905    34 Downloads   204 Views  

ABSTRACT

This study compares logit and probit regression models to analyze the likelihood of lung cancer occurrence based on patient data and lifestyle factors. The results reveal significant associations between lung cancer and patients’ age, gender, smoking status, yellow finger, anxiety, chronic disease, fatigue, allergy, wheezing, alcohol consumption, coughing, shortness of breath, swallowing difficulty, and chest pain. The result shows that the probit model better predicts lung cancer based on the factors observed as its diagnostic performs better than logit. Recommendations based on the findings emphasize the need to create awareness about the significant factors that influence lung cancer. Conclusively, this study contributes to a deeper understanding of the patient’s data and lifestyle factors influencing lung cancer and provides valuable insights.

Share and Cite:

Kasali, W.A. , Ogunjoun, B.O. , Olakehinde, A.O. , Oderinde, E.O. and Salam, A.O. (2024) Estimating the Likelihood of Cancer Occurrence Based on Patient Data and Lifestyle Factors: A Comparison between Logit and Probit Regression. Open Access Library Journal, 11, 1-11. doi: 10.4236/oalib.1111905.

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