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Uno studio della non autosufficienza a partire dai dati dell’Indagine Multiscopo: il caso dell’Umbria

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  • Giorgio E. Montanari

    ()
    (University of Perugia)

  • M. Giovanna Ranalli

    ()
    (University of Perugia)

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    Abstract

    This paper proposes a methodology for the estimation of the number of people that show a severe disability and are dependent, using data coming from the Italian National Survey on Health conditions and Appeal to Medicare. Dependency is treated as a latent trait hidden behind a set of items that survey difficulties in movements and in accomplishing everyday tasks (Activities of daily living). Latent class models are used to classify the population according to different levels of disability. The analysis provides a good classification using four classes. Looking at posterior probabilities, people belonging to each class may be labelled as being without disability, with light disability, with some dependence, with severe disability (dependent). The survey provides reliable estimates at regional – NUTS 2 – level. Estimating the amount of population within each latent class at sub-regional level, e.g. sanitary districts, requires small area estimation techniques. To this end, a multinomial unit level model is used with individual level covariates.

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    Bibliographic Info

    Article provided by ISTAT - Italian National Institute of Statistics - (Rome, ITALY) in its journal Rivista di Statistica Ufficiale.

    Volume (Year): 12 (2010)
    Issue (Month): 1 (April)
    Pages: 53-71

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    Handle: RePEc:isa:journl:v:12:y:2010:i:1:p:53-71

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    Related research

    Keywords: Latent variables; Latent Class Models; Small areas estimates;

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