We illustrate how latent Markov models may be used for the analysis of a longitudinal dataset coming from the administration of a set of dichotomously-scored items to a sample of elderly people admitted in different nursing homes. These models are aimed at describing individual changes in terms of quality of life, in particular considering: (i) how it changes over the time and (ii) how it depends on belonging to different nursing homes. For the maximum likelihood estimation we apply an EM algorithm which is implemented by means of certain recursions taken from the literature on hidden Markov models.

Latent Markov models for evaluating nursing home performances

LUPPARELLI, MONIA
2007

Abstract

We illustrate how latent Markov models may be used for the analysis of a longitudinal dataset coming from the administration of a set of dichotomously-scored items to a sample of elderly people admitted in different nursing homes. These models are aimed at describing individual changes in terms of quality of life, in particular considering: (i) how it changes over the time and (ii) how it depends on belonging to different nursing homes. For the maximum likelihood estimation we apply an EM algorithm which is implemented by means of certain recursions taken from the literature on hidden Markov models.
Complex Models and Computational intensive methods for estimation and prediction
44
49
F. Bartolucci; G.E. Montanari; M. Lupparelli
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/68207
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact