Accelerated failure time models in analyzing duration of employment

Abstract

Abstract Parametric accelerated failure time models (AFT), that assess the relationship between the event times and dependent variables constitute an essential class of regression models. In this research we have used the accelerated failure time models: in particular, we have taken into consideration exponential distribution, Weibull distribution, log-logistic model and lognormal distribution, to analyze the duration of employment for employees that have been in their current job or otherwise known as job tenure. A variety of commercial and public companies in Albania were surveyed for this study. Initially the goal of the research is to find the optimal probability distribution to suit the data. Then, the accelerated failure time model is used to assess the impact of the predictors, such as: the employee's age, wages, the employee's age when he has started the job, sex, profession, academic degree, marital status and years of experience prior to this position, in job termination. The log-normal AFT model was the most accurate model for predicting the outcomes of the study, and from this model we can conclude that the employee's age, the employee's age when he has started the job, wages, academic degree and position in the company can affect how long someone stays employed.