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Use of log‐skew‐normal distribution in analysis of continuous data with a discrete component at zero
Author(s) -
Chai High Seng,
Bailey Kent R.
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3210
Subject(s) - component (thermodynamics) , skew , zero (linguistics) , interpretation (philosophy) , data set , computer science , mathematics , distribution (mathematics) , continuous variable , statistics , algorithm , mathematical analysis , physics , telecommunications , linguistics , philosophy , thermodynamics , programming language
The problem of analyzing a continuous variable with a discrete component is addressed within the framework of the mixture model proposed by Moulton and Halsey ( Biometrics 1995; 51 :1570–1578). The model can be generalized by the introduction of the log‐skew‐normal distribution for the continuous component, and the fit can be significantly improved by its use, while retaining the interpretation of regression parameter estimates. Simulation studies and application to a real data set are used for demonstration. Copyright © 2008 John Wiley & Sons, Ltd.