http://www.cnr.it/ontology/cnr/individuo/prodotto/ID198354
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
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Federica Giardina; Alessandra Guglielmi; Fernando A Quintana; Fabrizio Ruggeri (literal)
- Pagina inizio
- Pagina fine
- 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
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Note
- 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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