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dc.contributor.authorGitau, Elizabeth
dc.date.accessioned2023-02-20T11:35:25Z
dc.date.available2023-02-20T11:35:25Z
dc.date.issued2022
dc.identifier.urihttp://erepository.uonbi.ac.ke/handle/11295/162735
dc.description.abstractThe goal of this project, is to compare the AFT model and Cox PH model using the employee attrition data set. Survival analysis examines the desired outcome until the occurrence of the event. Although Cox PH together with AFT models have been widely utilized in survival time predictions, AFT models are least used in employee attrition. Therefore, the goal of this research is to conduct survival analysis on the employee attrition data set to narrow down on the specific factors that will benefit the employer using both models and the best method to use. Using R, the Accelerated Failure Time model gave favourable outcome compared to the Cox PH model. The main factors that have a significant impact on the survival attrition include, the job role(Research Scientist, Sales Executive), home to job distance, work life balance, level of satisfaction in job and nature of travel. Furthermore, the Generalized Gamma AFT model offers the most outstanding fit for the observed data. The research will serve as a focal point for surviving analysis models in predicting employee attrition, enlightenment in the analysis and deepen the context of survival analysis.en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectComparing Accelerated Failure Timeen_US
dc.titleComparing Accelerated Failure Time and Cox Ph Models:a Case Study on Employee Attritionen_US
dc.typeThesisen_US
dc.description.departmenta Department of Psychiatry, University of Nairobi, ; bDepartment of Mental Health, School of Medicine, Moi University, Eldoret, Kenya


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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States