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Centile estimation for a proportion response variable
Authors:Abu Hossain  Robert Rigby  Mikis Stasinopoulos  Marco Enea
Institution:1. STORM, London Metropolitan University, London, U.K.;2. University of Palermo, Palermo, Italy
Abstract:This paper introduces two general models for computing centiles when the response variable Y can take values between 0 and 1, inclusive of 0 or 1. The models developed are more flexible alternatives to the beta inflated distribution. The first proposed model employs a flexible four parameter logit skew Student t ( logitSST ) distribution to model the response variable Y on the unit interval (0, 1), excluding 0 and 1. This model is then extended to the inflated logitSST distribution for Y on the unit interval, including 1. The second model developed in this paper is a generalised Tobit model for Y on the unit interval, including 1. Applying these two models to (1‐Y) rather than Y enables modelling of Y on the unit interval including 0 rather than 1. An application of the new models to real data shows that they can provide superior fits. Copyright © 2015 John Wiley & Sons, Ltd.
Keywords:beta inflated distribution  fractional data  GAMLSS  generalised Tobit model  logit skew Student t distribution
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