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Articles

On bootstrap testing inference in cure rate models

ORCID Icon, & ORCID Icon
Pages 3437-3454 | Received 05 Mar 2018, Accepted 07 Sep 2018, Published online: 16 Sep 2018

References

  • Lawless J. Statistical models and methods for lifetime data. 2nd ed. Hoboken: John Wiley & Sons; 2003.
  • Maller R, Zhou XSurvival analysis with long-term survivors. New York: John Wiley & Sons; 1996.
  • Chen MH, Ibrahim JG. Maximum likelihood methods for cure rate models with missing covariates. Biometrics. 2001;57(1):43–52. doi: 10.1111/j.0006-341X.2001.00043.x
  • Yin G, Ibrahim JG. Cure rate models: a unified approach. Can J Stat. 2005;33(4):559–570. doi: 10.1002/cjs.5550330407
  • Rodrigues J, Cancho VG, de Castro M, et al. On the unification of long-term survival models. Stat Probab Lett. 2009;79(6):753–759. doi: 10.1016/j.spl.2008.10.029
  • Rodrigues J, Cordeiro GM, Cancho VG, et al. Relaxed poisson cure rate models. Biom J. 2015;58(2):397–415. doi: 10.1002/bimj.201500051
  • Boag J. Maximum likelihood estimates of the proportion of patients cured by cancer therapy. J R Stat Soc Series B (Methodological). 1949;11(1):15–53.
  • Berkson J, Gage R. Survival curve for cancer patients following treatment. J Am Stat Assoc. 1952;47(259):501–515. doi: 10.1080/01621459.1952.10501187
  • Yakovlev A, Tsodikov A. Stochastic models of tumor latency and their biostatistical applications. Singapore: World Scientific; 1996.
  • Yakovlev A, Asselain B, Bardou V, et al. A simple stochastic model of tumor recurrence and its application to data on premenopausal breast cancer. Biometrie et Analyse de Donnees Spatio-temporelles. 1993;12:66–82.
  • Chen M, Ibrahim J, Sinha D. A new Bayesian model for survival data with a surviving fraction. J Am Stat Assoc. 1999;94(449):909–919. doi: 10.1080/01621459.1999.10474196
  • Zeng D, Yin G, Ibrahim JG. Semiparametric transformation models for survival data with a cure fraction. J Am Stat Assoc. 2006;101(474):670–684. doi: 10.1198/016214505000001122
  • Tournoud M, Ecochard R. Promotion time models with time-changing exposure and heterogeneity: application to infectious diseases. Biom J. 2008;50(3):395–407. doi: 10.1002/bimj.200710405
  • Fonseca RS, Valença DM, Bolfarine H. Cure rate survival models with missing covariates: a simulation study. J Stat Comput Simul. 2013;83(1):97–113. doi: 10.1080/00949655.2011.613396
  • Ibrahim JG, Chen MH, Sinha D. Bayesian survival analysis. New York: John Wiley & Sons; 2005.
  • Neyman J, Pearson ES. On the use and interpretation of certain test criteria for purposes of statistical inference. Biometrika. 1928;20(1/2):175–240. doi: 10.2307/2331945
  • Wald A. Tests of statistical hypotheses concerning several parameters when the number of observations is large. Trans Am Math Soc. 1943;54(3):426–482. doi: 10.1090/S0002-9947-1943-0012401-3
  • Rao C. Large sample tests of statistical hypotheses concerning several parameters with applications to problems of estimation. Math Proc Camb Philos Soc. 1948;44(01):50–57. doi: 10.1017/S0305004100023987
  • Terrell G. The gradient statistic. Comput Sci Stat. 2002;34:206–215.
  • Cordeiro GM, Cribari-Neto F. An introduction to bartlett correction and bias reduction. New York: Springer; 2014.
  • Cribari-Neto F, Cordeiro GM. On Bartlett and Bartlett-type corrections. Econom Rev. 1996;15(4):339–367. doi: 10.1080/07474939608800361
  • Carneiro HP, Valença DM. Gradient and likelihood ratio tests in cure rate models. Int J Stat Probab. 2016;5(4):9. doi: 10.5539/ijsp.v5n4p9
  • Efron B. Bootstrap methods: another look at the jackknife. Ann Stat. 1979;7(1):1–26. doi: 10.1214/aos/1176344552
  • Cribari-Neto F, Queiroz MP. On testing inference in beta regressions. J Stat Comput Simul. 2014;84(1):186–203. doi: 10.1080/00949655.2012.700456
  • Barreto LS, Cysneiros AHMA, Cribari-Neto F. Improved Birnbaum-Saunders inference under type II censoring. Comput Stat Data Anal. 2013;57(1):68–81. doi: 10.1016/j.csda.2012.06.005
  • Rocke DM. Bootstrap Bartlett adjustment in seemingly unrelated regression. J Am Stat Assoc. 1989;84(406):598–601. doi: 10.1080/01621459.1989.10478809
  • Lawley DN. A general method for approximating to the distribution of likelihood ratio criteria. Biometrika. 1956;43(3/4):295–303. doi: 10.2307/2332908
  • Loose LH, Bayer FM, Pereira TL. Bootstrap Bartlett correction in inflated beta regression. Commun Stat Simul Comput. 2017;46(4):2865–2879. doi: 10.1080/03610918.2015.1065326
  • Press W, Teukolsky S, Vetterling W, et al. Numerical recipes in C: the art of scientific computing. Cambridge: Cambridge University University Press; 1992.
  • Sen PK, Singer JM. Large sample methods in statistics: an introduction with applications. Vol. 25. New York: Chapman & Hall; 1994.
  • Severini TA. Likelihood methods in statistics. Vol. 22. Oxford: Oxford University Press; 2000.
  • Beran R. Prepivoting test statistics: a bootstrap view of asymptotic refinements. J Am Stat Assoc. 1988;83(403):687–697. doi: 10.1080/01621459.1988.10478649
  • Davison AC, Hinkley DV. Bootstrap methods and their application. Vol. 1. Cambridge: Cambridge University Press; 1997.
  • Bayer F, Cribari-Neto F. Bartlett corrections in beta regression models. J Stat Plan Inference. 2013;143(3):531–547. doi: 10.1016/j.jspi.2012.08.018
  • Bartlett MS. Properties of sufficiency and statistical tests. R Soc London Proc Series A. 1937;160(901):268–282. doi: 10.1098/rspa.1937.0109
  • Heller G, Venkatraman E. Resampling procedures to compare two survival distributions in the presence of right-censored data. Biometrics. 1996;52(4):1204–1213. doi: 10.2307/2532836
  • Reid N. Estimating the median survival time. Biometrika. 1981;68(3):601–608. doi: 10.1093/biomet/68.3.601
  • Efron B. Censored data and the bootstrap. J Am Stat Assoc. 1981;76(374):312–319. doi: 10.1080/01621459.1981.10477650
  • Akritas MG. Bootstrapping the Kaplan-Meier estimator. J Am Stat Assoc. 1986;81(396):1032–1038.
  • Pardo-Fernández JC, Van Keilegom I, González-Manteiga W. Goodness-of-fit tests for parametric models in censored regression. Can J Stat. 2007;35(2):249–264. doi: 10.1002/cjs.5550350204
  • Orbe J, Ferreira E, Nunez-Anton V. Censored partial regression. Biostatistics. 2003;4(1):109–121. doi: 10.1093/biostatistics/4.1.109
  • R Development Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2014. ISBN 3-900051-07-0.
  • Viana MB, Murao M, Ramos G, et al. Malnutrition as a prognostic factor in lymphoblastic leukaemia: a multivariate analysis. Arch. Dis. Child.. 1994;71(4):304–310. doi: 10.1136/adc.71.4.304
  • Cox DR. Regression models and life tables (with discussion). J R Stat Soc B. 1972;3(4):527–541.
  • Sala A, Pencharz P, Barr RD. Children, cancer, and nutrition a dynamic triangle in review. Cancer. 2004;100(4):677–687. doi: 10.1002/cncr.11833

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