We compare two alternative approaches of modeling longitudinal data in order to find patterns of change according to the available covariates, accounting for the unobserved heterogeneity in the population of interest. We refer to the Latent Markov (LM) model and to the Growth Mixture Model (GMM). We illustrate the main results by using real data on the self-perceived health status.

Pennoni, F., Romeo, I. (2015). Latent Markov and growth mixture models: a comparison. In Book of Abstract of the 10th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (SIS) (pp.181-184). Cagliari : CUEC.

Latent Markov and growth mixture models: a comparison

PENNONI, FULVIA;ROMEO, ISABELLA
2015

Abstract

We compare two alternative approaches of modeling longitudinal data in order to find patterns of change according to the available covariates, accounting for the unobserved heterogeneity in the population of interest. We refer to the Latent Markov (LM) model and to the Growth Mixture Model (GMM). We illustrate the main results by using real data on the self-perceived health status.
abstract + slide
EM algorithm, measurement error models, ordinal variables
English
CLADAG 2015 10° Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society
2015
Mola, F; Conversano, C
Book of Abstract of the 10th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (SIS)
978-88-8467-949-9
2015
1
181
184
none
Pennoni, F., Romeo, I. (2015). Latent Markov and growth mixture models: a comparison. In Book of Abstract of the 10th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (SIS) (pp.181-184). Cagliari : CUEC.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

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/10281/92380
Citazioni
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
Social impact