Transform both sides model: A parametric approach

A. Polpo, C. P. de Campos, D. Sinha, S. Lipsitz, J. Lin

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

A parametric regression model for right-censored data with a log-linear median regression function and a transformation in both response and regression parts, named parametric Transform-Both-Sides (TBS) model, is presented. The TBS model has a parameter that handles data asymmetry while allowing various different distributions for the error, as long as they are unimodal symmetric distributions centered at zero. The discussion is focused on the estimation procedure with five important error distributions (normal, double-exponential, Student's t, Cauchy and logistic) and presents properties, associated functions (that is, survival and hazard functions) and estimation methods based on maximum likelihood and on the Bayesian paradigm. These procedures are implemented in TBSSurvival, an open-source fully documented R package. The use of the package is illustrated and the performance of the model is analyzed using both simulated and real data sets.
Original languageEnglish
Pages (from-to)903-913
Number of pages11
JournalComputational Statistics & Data Analysis
Volume71
Early online date22 Jul 2013
DOIs
Publication statusPublished - Mar 2014

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