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A comparison of the Hosmer-Lemeshow, Pigeon-Heyse, and Tsiatis goodness-of-fit tests for binary logistic regression under two grouping methods

Citation

Canary, JD and Blizzard, L and Barry, RP and Hosmer, DW and Quinn, SJ, A comparison of the Hosmer-Lemeshow, Pigeon-Heyse, and Tsiatis goodness-of-fit tests for binary logistic regression under two grouping methods, Communications in Statistics: Simulation and Computation, 46, (3) pp. 1871-1894. ISSN 0361-0918 (2017) [Refereed Article]

Copyright Statement

Copyright 2017 Taylor & Francis Group, LLC

DOI: doi:10.1080/03610918.2015.1017583

Abstract

Algebraic relationships between Hosmer–Lemeshow (HL), Pigeon–Heyse (J2), and Tsiatis (T) goodness-of-fit statistics for binary logistic regression models with continuous covariates were investigated, and their distributional properties and performances studied using simulations. Groups were formed under deciles-of-risk (DOR) and partition-covariate-space (PCS) methods. Under DOR, HL and T followed reported null distributions, while J2 did not. Under PCS, only T followed its reported null distribution, with HL and J2 dependent on model covariate number and partitioning. Generally, all had similar power. Of the three, T performed best, maintaining Type-I error rates and having a distribution invariant to covariate characteristics, number, and partitioning.

Item Details

Item Type:Refereed Article
Keywords:binary logistic regression, deciles-of-risk, goodness-of-fit, Hosmer-Lemeshow, partition the covariate space, Pigeon-Heyse, Tsiatis
Research Division:Mathematical Sciences
Research Group:Statistics
Research Field:Statistics not elsewhere classified
Objective Division:Health
Objective Group:Other Health
Objective Field:Health not elsewhere classified
UTAS Author:Canary, JD (Dr Jana Canary)
UTAS Author:Blizzard, L (Professor Leigh Blizzard)
ID Code:124595
Year Published:2017
Web of Science® Times Cited:2
Deposited By:Menzies Institute for Medical Research
Deposited On:2018-02-28
Last Modified:2018-07-20
Downloads:0

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