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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18581

Title: Semi-parametric Bayesian analysis of binary responses with a continuous covariate subject to non-random missingness
Authors: Poleto, Frederico Z.
Paulino, Carlos Daniel
Singer, Julio M.
Molenberghs, Geert
Issue Date: 2015
Citation: STATISTICAL MODELLING, 15 (1), p. 1-23
Abstract: Missingness in explanatory variables requires a model for the covariates even if the interest lies only in a model for the outcomes given the covariates. An incorrect specification of the models for the covariates or for the missingness mechanism may lead to biased inferences for the parameters of interest. Previously published articles either use semi-/non-parametric flexible distributions for the covariates and identify the model via a missing at random assumption, or employ parametric distributions for the covariates and allow a more general non-random missingness mechanism. We consider the analysis of binary responses, combining a missing not at random mechanism with a nonparametric model based on a Dirichlet process mixture for the continuous covariates. We illustrate the proposal with simulations and the analysis of a dataset.
Notes: Address for correspondence: Frederico Z. Poleto, Instituto de Matemática e Estatística, Universidade de Saao Paulo, Caixa Postal 66281, Saao Paulo, SP, 05314-970, Brazil. E-mail: frederico@poleto.com
URI: http://hdl.handle.net/1942/18581
Link to publication: https://lirias.kuleuven.be/bitstream/123456789/489600/4/428.pdf
DOI: 10.1177/1471082X14549290
ISI #: 000349621700002
ISSN: 1471-082X
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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