Bayesian first order autoregressive latent variable models for multiple binary sequences (Articolo in rivista)

Type
Label
  • Bayesian first order autoregressive latent variable models for multiple binary sequences (Articolo in rivista) (literal)
Anno
  • 2011-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1177/1471082X1001100601 (literal)
Alternative label
  • Federica Giardina; Alessandra Guglielmi; Fernando A Quintana; Fabrizio Ruggeri (2011)
    Bayesian first order autoregressive latent variable models for multiple binary sequences
    in Statistical modelling; Sage, London (Regno Unito)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Federica Giardina; Alessandra Guglielmi; Fernando A Quintana; Fabrizio Ruggeri (literal)
Pagina inizio
  • 471 (literal)
Pagina fine
  • 488 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://smj.sagepub.com/content/11/6/471 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 11 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 6 (literal)
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Swiss Tropical and Public Health Institute, Basel, Switzerland; Politecnico di Milano, Milano, Italy; CNR-IMATI, Milano, Italy; Pontificia Universidad Católica de Chile, Santiago, Chile (literal)
Titolo
  • Bayesian first order autoregressive latent variable models for multiple binary sequences (literal)
Abstract
  • Longitudinal clinical trials often collect long sequences of binary data monitoring a disease process over time. Our application is a medical study conducted in the US by the Veterans Administration Cooperative Urological Research Group to assess the effectiveness of a chemotherapy treatment (thiotepa) in preventing recurrence on subjects affected by bladder cancer. We propose a generalized linear model with latent auto-regressive structure for longitudinal binary data following a Bayesian approach. We discuss inference as well as sensitivity to prior choices for the bladder cancer data. We find that there is a significant treatment effect in the sense that treated patients have much smaller predicted recurrence probabilities than placebo patients. (literal)
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