Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16124
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dc.contributor.authorNYSEN, Ruth-
dc.contributor.authorAERTS, Marc-
dc.contributor.authorFAES, Christel-
dc.date.accessioned2014-01-10T10:34:04Z-
dc.date.available2014-01-10T10:34:04Z-
dc.date.issued2011-
dc.identifier.citationConesa, David; Forte, Anabel; López-Quílez, Antonio; Muñoz, Facundo (Ed.). Proceedings of the 26th International Workshop on Statisical Modelling, p. 441-444-
dc.identifier.isbn978-84-694-5129-8-
dc.identifier.urihttp://hdl.handle.net/1942/16124-
dc.description.abstractA goodness-of-fit test for left-, right- and interval-censored data, assuming random censorship is proposed and studied. In the first step of the test, the null model is extended to a series of nested alternative models for censored data as in Zhang and Davidian (2008). Then a modified AIC model selection is used to select the best model to describe the data. If a model with one or more extra parameters is selected, then the null hypothesis is rejected. This new goodness-of-fit test procedure is based on the order selection test as described in Aerts, Claeskens and Hart (1999). The applicability of the test is illustrated in the context of microbial agents, and its performance characteristics are demonstrated through simulation studies.-
dc.language.isoen-
dc.subject.otherGoodness-of-fit test; Censored data; SNP estimator; Order selection test-
dc.titleTesting Goodness-of-Fit of Parametric Models for Censored Data-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsConesa, David-
local.bibliographicCitation.authorsForte, Anabel-
local.bibliographicCitation.authorsLópez-Quílez, Antonio-
local.bibliographicCitation.authorsMuñoz, Facundo-
local.bibliographicCitation.conferencedate11 July 2011 - 15 July 2011-
local.bibliographicCitation.conferencename26th International Workshop on Statisical Modelling-
local.bibliographicCitation.conferenceplaceValencia, Spain-
dc.identifier.epage444-
dc.identifier.spage441-
local.bibliographicCitation.jcatC1-
dc.relation.referencesAerts, M., Claeskens, G. and Hart, J. (1999). Testing the fit of a parametric function. Journal of the American Statistical Association, 94, 869-879. Calle, M. L. and Gómez, G. (2008) Statistical models and methods for biomedical and technical systems Birkh auser Boston Cao, J., Moosman, A. and Johnson, V. E. (2010). A Bayesian Chi-Squared Goodness-of-Fit Test for Censored Data Models. Biometrics, 66, 426-434. Hollander, M. and Proschan, F. (1979). Testing to determine the underlying distribution using randomly censored data. Biometrics, 35(2), 393-401. Ren, J. (2003). Goodness of fit tests with interval censored data, Scandinavian Journal of Statistics. Theory and Applications, 30(1), 211-226. Yin, G. (2009). Bayesian goodness-of-fit test for censored data. Journal of Statistical Planning and Inference, 139(4), 1474-1483. Zhang, M., Davidian, M. (2008). Smooth semiparametric regression analysis for arbitrarily censored time-to-event data. Biometrics, 64, 567-669.-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.bibliographicCitation.btitleProceedings of the 26th International Workshop on Statisical Modelling-
item.accessRightsOpen Access-
item.fullcitationNYSEN, Ruth; AERTS, Marc & FAES, Christel (2011) Testing Goodness-of-Fit of Parametric Models for Censored Data. In: Conesa, David; Forte, Anabel; López-Quílez, Antonio; Muñoz, Facundo (Ed.). Proceedings of the 26th International Workshop on Statisical Modelling, p. 441-444.-
item.contributorNYSEN, Ruth-
item.contributorAERTS, Marc-
item.contributorFAES, Christel-
item.fulltextWith Fulltext-
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