Inference on zero inflated ordinal models with semiparametric link

Ujjwal Das and Kalyan Das

Computational Statistics & Data Analysis, 2018, vol. 128, issue C, 104-115

Abstract: In socioeconomics or in Biological studies, observations on individuals are often observed longitudinally on a Likert-type scale with substantially large proportion of zeros. This leads to a special case of mixture structured data where extra-variation occurs. Obviously the standard ordinal data analysis fails to provide appropriate statistical inference. We propose a suitable zero inflated semiparametric ordinal model that takes into account the non linear link between the ordinal response and a covariate. A sieve maximum likelihood estimator(MLE) is proposed for the regression parameter of interest. We also propose a test for the zero proportion in this semiparametric model. A simulation study has been carried out to investigate the performance of the estimator as well as the test. We illustrate the methodology using data from a survey on Tuberculosis patients in and around Kolkata, India.

Keywords: Ordinal data; Zero inflation; Semiparametric regression; Knot selection; Sieve MLE (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:128:y:2018:i:c:p:104-115

DOI: 10.1016/j.csda.2018.06.016

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