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Inference on zero inflated ordinal models with semiparametric link

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  • Das, Ujjwal
  • Das, Kalyan

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.

Suggested Citation

  • Das, Ujjwal & Das, Kalyan, 2018. "Inference on zero inflated ordinal models with semiparametric link," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 104-115.
    • Handle: RePEc:eee:csdana:v:128:y:2018:i:c:p:104-115
    DOI: 10.1016/j.csda.2018.06.016
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    References listed on IDEAS

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    Cited by:

    1. Ujjwal Das & Kalyan Das, 2021. "Selection of influential variables in ordinal data with preponderance of zeros," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(1), pages 66-87, February.
    2. Cristian Roner & Claudia Di Caterina & Davide Ferrari, 2021. "Exponential Tilting for Zero-inflated Interval Regression with Applications to Cyber Security Survey Data," BEMPS - Bozen Economics & Management Paper Series BEMPS85, Faculty of Economics and Management at the Free University of Bozen.

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