Discrete Weibull regression for modeling football outcomes

Bayesian Isotonic Regression for Discrete Outcomes

1 SUMMARY. This article proposes a semiparametric Bayesian approach for inference on an unknown isotonic regression function, f (x), characterizing the relationship between a continuous predictor, X, and a response variable, Y , adjusting for covariates, Z. A novel prior formulation is used, which avoids parametric assumptions on f (x), while enforcing the non-decreasing constraint and assignin...

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

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...

Modeling adverse birth outcomes via confirmatory factor quantile regression.

We describe a Bayesian quantile regression model that uses a confirmatory factor structure for part of the design matrix. This model is appropriate when the covariates are indicators of scientifically determined latent factors, and it is these latent factors that analysts seek to include as predictors in the quantile regression. We apply the model to a study of birth weights in which the effect...