6533b82cfe1ef96bd128e976
RESEARCH PRODUCT
Centile estimation for a proportion response variable
Robert A. RigbyMikis D. StasinopoulosMarco EneaAbu Hossainsubject
Statistics and ProbabilityEstimationDistribution (number theory)EpidemiologyLogitSkew01 natural sciences010104 statistics & probability03 medical and health sciencesVariable (computer science)0302 clinical medicineUnit interval (data transmission)030225 pediatricsStatisticsProbability distributionTobit model0101 mathematicsMathematicsdescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-10-04 | Statistics in Medicine |