Mostra el registre d'ítem simple
Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data
dc.contributor.author | Serrat Piè, Carles |
dc.contributor.author | Rué, Montserrat |
dc.contributor.author | Armero, Carmen |
dc.contributor.author | Piulachs Lozada Benavente, Xavier |
dc.contributor.author | Perpiñán Fabuel, Hèctor |
dc.contributor.author | Forte, Anabel |
dc.contributor.author | Páez, Álvaro |
dc.contributor.author | Gómez Melis, Guadalupe |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Matemàtiques |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa |
dc.date.accessioned | 2016-04-01T07:49:01Z |
dc.date.available | 2016-04-01T07:49:01Z |
dc.date.issued | 2015-06-03 |
dc.identifier.citation | Serrat, C., Rué, M., Armero, C., Piulachs, X., Perpiñán, H., Forte, A., Páez, Á., Gomez, G. Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data. "Journal of Applied Statistics", 03 Juny 2015, vol. 42, núm. 6, p. 1223-1239. |
dc.identifier.issn | 0266-4763 |
dc.identifier.uri | http://hdl.handle.net/2117/85035 |
dc.description.abstract | The paper describes the use of frequentist and Bayesian shared-parameter joint models of longitudinal measurements of prostate-specific antigen (PSA) and the risk of prostate cancer (PCa). The motivating dataset corresponds to the screening arm of the Spanish branch of the European Randomized Screening for Prostate Cancer study. The results show that PSA is highly associated with the risk of being diagnosed with PCa and that there is an age-varying effect of PSA on PCa risk. Both the frequentist and Bayesian paradigms produced very close parameter estimates and subsequent 95% confidence and credibility intervals. Dynamic estimations of disease-free probabilities obtained using Bayesian inference highlight the potential of joint models to guide personalized risk-based screening strategies. |
dc.format.extent | 17 p. |
dc.language.iso | eng |
dc.publisher | Taylor & Francis |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica |
dc.subject.lcsh | Survival analysis (Biometry) |
dc.subject.other | 62P10 |
dc.subject.other | 62N01 |
dc.subject.other | relative risk models |
dc.subject.other | linear mixed models |
dc.subject.other | shared-parameter models |
dc.subject.other | prostate cancer screening |
dc.subject.other | joint models |
dc.subject.other | TO-EVENT DATA |
dc.subject.other | LATENT CLASS MODELS |
dc.subject.other | DISEASE PROGRESSION |
dc.subject.other | FOLLOW-UP |
dc.subject.other | TIME |
dc.subject.other | MORTALITY |
dc.subject.other | SURVIVAL |
dc.subject.other | FAILURE |
dc.subject.other | PSA |
dc.subject.other | PREDICTION |
dc.title | Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data |
dc.type | Article |
dc.subject.lemac | Anàlisi de supervivència (Biometria) |
dc.contributor.group | Universitat Politècnica de Catalunya. GRBIO - Grup de Recerca en Bioestadística i Bioinformàtica |
dc.identifier.doi | 10.1080/02664763.2014.999032 |
dc.description.peerreviewed | Peer Reviewed |
dc.rights.access | Open Access |
local.identifier.drac | 15536485 |
dc.description.version | Postprint (author's final draft) |
local.citation.author | Serrat, C.; Rué, M.; Armero, C.; Piulachs, X.; Perpiñán, H.; Forte, A.; Páez, Á.; Gomez, G. |
local.citation.publicationName | Journal of Applied Statistics |
local.citation.volume | 42 |
local.citation.number | 6 |
local.citation.startingPage | 1223 |
local.citation.endingPage | 1239 |
Fitxers d'aquest items
Aquest ítem apareix a les col·leccions següents
-
Articles de revista [213]
-
Articles de revista [3.226]
-
Articles de revista [712]