The Log Beta Generalized Weibull Regression Model for Lifetime Data

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likel...

Random effects Weibull regression model for occupational lifetime

The Log-Beta Weibull Regression Model with Application to Predict Recurrence of Prostate Cancer

We study the properties of the called log-beta Weibull distribution defined by the logarithm of the beta Weibull random variable (Famoye et al., 2005; Lee et al., 2007). An advantage of the new distribution is that it includes as special sub-models classical distributions reported in the lifetime literature. We obtain formal expressions for the moments, moment generating function, quantile func...

Bayesian paradigm for analysing count data in longitudina studies using Poisson-generalized log-gamma model

In analyzing longitudinal data with counted responses, normal distribution is usually used for distribution of the random efffects. However, in some applications random effects may not be normally distributed. Misspecification of this distribution may cause reduction of efficiency of estimators. In this paper, a generalized log-gamma distribution is used for the random effects which includes th...

Stratified Weibull Regression Model for Interval-Censored Data.

Interval censored outcomes arise when a silent event of interest is known to have occurred within a specific time period determined by the times of the last negative and first positive diagnostic tests. There is a rich literature on parametric and non-parametric approaches for the analysis of interval-censored outcomes. A commonly used strategy is to use a proportional hazards (PH) model with t...