Open Conference Systems, 50th Scientific meeting of the Italian Statistical Society

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Zero-inflated ordinal data models with application to sport (in)activity
Maria Iannario, Rosaria Simone

Last modified: 2018-05-17

Abstract


Traditional models for ordinal data (as CUB models or cumulative models with logit/probit link, among others) present limits in explaining the surplus of zero observations, especially when the zeros may relate to two distinct situations of non-participation/inactivity and infrequent participation, for instance. We consider an extension of standard models: zero-inflated CUB models and zero inflated ordered cumulative (ZIOC) probit/logit models handling the GECUB models and usinga double-hurdle combination of a split (logit/probit) model and an ordered probit/logit models, respectively. Both extensions, potentially, relate to different sets of covariates. Finally, models are applied to Sport surveys. Specifically the paper investigates the determinants of sport (in)activity: the frequency and the probabilityof sports participation. It distinguishes between genuine “non-participants†and the ones who do not participate at a time but might under different circumstances.

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