||Achim D, Emura T (2019), Analysis of Doubly Truncated Data, An Itroduction, JSS Research Series in Statistics, Springer, Singapore.|
Belaghi RA, Asl MN (2016) Estimation based on progressively type-I hybrid censored data from the Burr XII distribution. Stat Pap doi: 10.1007/s00362-016-0849-5.
Burr IW (1942) Cumulative frequency functions. Ann Math Stat 13(2), 215-232.
Clayton DG (1978) A model for association in bivariate life tables and its application to epidemiological studies of familial tendency in chronic disease incidence. Biometrika. 65, 141-51
Crowder MJ (2012) Multivariate Survival Analysis and Competing Risks, CRC Press, New York.
David HA, Moeschberger ML (1978) The Theory of Competing Risks. London: Griffin.
Duchateau L, Janssen P (2008) The Frailty Model. Berlin: Springer.
Duchateau L, Janssen P, Lindsey P, Legrand C, Nguti R, Sylvester R (2002) The shared frailty model and the power for heterogeneity tests in multicenter trials. Comp Stat Data Anal, 40(3), 603-620.
Emura T, Chen YH (2016) Gene selection for survival data under dependent censoring, a copula-based approach, Stat Methods Med Res 25(6): 2840-57.
Emura T, Michimae H (2017) A copula-based inference to piecewise exponential models under dependent censoring, with application to time to metamorphosis of salamander larvae, Environ Ecol Stat 24(1) 151–73.
Emura T, Nakatochi M, Murotani K, Rondeau V (2017) A joint frailty-copula model between tumour progression and death for meta-analysis, Stat Methods Med Res 26: 2649-66.
Emura T, Nakatochi M, Matsui S, Michimae H, Rondeau V (2018) Personalized dynamic prediction of death according to tumour progression and high-dimensional genetic factors: meta-analysis with a joint model, Stat Methods Med Res 27(9):2842-58
Emura T, Matsui S, Rondeau V (2019a) Survival Analysis with Correlated Endpoints, Joint Frailty-Copula Models, Springer, Singapore.
Emura T, Pan CH (2017), Parametric maximum likelihood inference and goodness-of-fit tests for dependently left-truncated data, a copula-based approach, Stat Pap, doi:10.1007/s00362-017-0947-z
Emura T, Shih JH, Ha ID, Wilke R (2019b) Comparison between the marginal hazard models and sub-distribution hazard models for competing risks data, in revision.
Emura T, Wang H (2010) Approximate tolerance limits under the log-location-scale models in the presence of censoring, Technometrics 52(3): 313-23
Escarela G, Carriere JF (2003) Fitting competing risks with an assumed copula. Stat Methods Med Res 12: 333-349.
Fan TH, Wang YF, Ju SK (2019). A competing risks model with multiply censored reliability data under multivariate Weibull distributions. IEEE Transactions on Reliability doi: 10.1109/TR.2019.2907518.
Gumbel EJ (1960) Distributions de valeurs extremes en plusieurs dimensions. PubL Inst Statist. Parids 9: 171-173.
He Z, Emura T (2019), Likelihood inference under the COM-Poisson cure model for survival data - computational aspects, J Chinese Stat Assoc 57: 1-42.
Hougaard P (1984) Life Table Methods for Heterogeneous Populations: Distributions Describing the Heterogeneity. Biometrika 71:75-83.
Kayid M, Noughabi, MS, Abouammoh AM (2019). A nonparametric estimator of bivariate quantile residual life model with application to tumor recurrence data set. Journal of Classification, 1-17.
Kotz S, Balakrishnan N, Johnson NL (2000) Continuous Multivariate Distributions, Volume 1: Models and Applications, Wiley, New York.
Leone FC, Nelson LS, Nottingham RB (1961) The Folded Normal Distribution. Technometrics 3(4),543-550.
Lim JY, Jeong JH (2017) Cause-specific quantile residual life regression. Stat Methods Med Res, 26(4), 1912-1924.
Liu X (2012) Planning of accelerated life tests with dependent failure modes based on a gamma frailty model. Technometrics 54(4), 398-409.
Lo SM, Stephan G, Wilke RA (2017) Competing risks copula models for unemployment duration: An application to a German Hartz reform. Journal of Econometric Methods 6(1):1-20.
Lu JC, Bhattacharyya GK (1990) Some new constructions of bivariate weibull models. Annals of the Institute of Statistical Mathematics 42:543–559.
MacDonald LL (2014) Does Newton-Raphson really fail? Stat Methods Med Res 23(3):308-311.
Mendenhall W, Hader RJ (1958) Estimation of parameters of mixed exponential distributed failure time distribution from censored life test data. Biometrika 45, 504-520.
Noughabi MS, Kayid M (2017). Bivariate quantile residual life: a characterization theorem and statistical properties. Stat Pap DOI:10.1007/s00362-017-0905-9.
Oakes D (1989). Bivariate Survival Models Induced by Frailties. JASA 84:487-493.
Peng M, Xiang L, Wang S (2018) Semiparametric regression analysis of clustered survival data with semi-competing risks, Comp Stat Data Anal 124: 53-70.
Rotolo T, Legrand C, Van Keilegom I (2013) A simulation procedure based on copulas to generate clustered multi-state survival data. Comput Methods Programs Biomed 109(3): 305-312.
Shih JH, Emura T (2016) Bivariate dependence measures and bivariate competing risks models under the generalized FGM copula. Stat Pap. doi: 10.1007/s00362-016-0865-5.
Shih JH, Emura T (2018) Likelihood-based inference for bivariate latent failure time models with competing risks under the generalized FGM copula, Comput Stat 33(3): 1293-23.
Shih JH, Lee W, Sun LH, Emura T (2018) Fitting competing risks data to bivariate Pareto models, Commun Stat-Theor 48(5), 1193-1220.
Watkins AJ (1999) An algorithm for maximum likelihood estimation in the three parameter Burr XII distribution. Comp Stat Data Anal 32(1), 19-27.
Zhang C, Pan L, Wang S, Wang X (2018) An accelerated life test model for solid lubricated bearings used in space based on time-varying dependence analysis of different failure modes. Acta Astronautica 152:352-359.
Zheng M, Klein JP (1995) Estimates of marginal survival for dependent competing risks based on an assumed copula. Biometrika 82(1), 127-138.
Zhou Y, Lu Z, Shi Y, Cheng K (2018) The copula-based method for statistical analysis of step-stress accelerated life test with dependent competing failure modes. Proc. Inst. Mech. Eng, Part O: Journal of Risk and Reliability 1748006X18793251.
Zimmer WJ, Keats JB, Wang FK (1998) The Burr XII Distribution in Reliability Analysis Journal of Quality Technology 30(4):386-394.