User menu

Semi-parametric frailty model for clustered interval-censored data

Bibliographic reference Cetinyürek, Aysun ; Lambert, Philippe. Semi-parametric frailty model for clustered interval-censored data. In: Statistical Modelling : an international journal, Vol. 16, no.5, p. 360-391 (2016)
Permanent URL http://hdl.handle.net/2078.1/177215
  1. Aalen Odd O., Heterogeneity in survival analysis, 10.1002/sim.4780071105
  2. Agresti Alan, Caffo Brian, Ohman-Strickland Pamela, Examples in which misspecification of a random effects distribution reduces efficiency, and possible remedies, 10.1016/j.csda.2003.12.009
  3. Atchadé Yves F., Rosenthal Jeffrey S., On adaptive Markov chain Monte Carlo algorithms, 10.3150/bj/1130077595
  4. Bellamy Scarlett L., Li Yi, Ryan Louise M., Lipsitz Stuart, Canner Marina J., Wright Rosalind, Analysis of clustered and interval censored data from a community-based study in asthma, 10.1002/sim.1918
  5. Cai Tianxi, Betensky Rebecca A., Hazard Regression for Interval-Censored Data with Penalized Spline, 10.1111/1541-0420.00067
  6. Çetinyürek Yavuz Aysun, Lambert Philippe, Smooth estimation of survival functions and hazard ratios from interval-censored data using Bayesian penalized B-splines, 10.1002/sim.4081
  7. Chen J., A Monte Carlo EM algorithm for generalized linear mixed models with flexible random effects distribution, 10.1093/biostatistics/3.3.347
  8. CLAYTON D. G., A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence, 10.1093/biomet/65.1.141
  9. Clayton D, Proceedings of the Centenary Session of the International Statistical Institute, 47, 467 (1985)
  10. Cowles Mary Kathryn, Carlin Bradley P., Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review, 10.1080/01621459.1996.10476956
  11. Eilers Paul HC, Ill-posed problems with counts, the composite link model and penalized likelihood, 10.1177/1471082x0700700302
  12. Eilers Paul H. C., Marx Brian D., Flexible smoothing with B -splines and penalties, 10.1214/ss/1038425655
  13. Eilers Paul H. C., Marx Brian D., Splines, knots, and penalties, 10.1002/wics.125
  14. Finkelstein Dianne M., A Proportional Hazards Model for Interval-Censored Failure Time Data, 10.2307/2530698
  15. Gelman A, Bayesian Statistics, 5, 599 (1996)
  16. Gelman Andrew, Rubin Donald B., Inference from Iterative Simulation Using Multiple Sequences, 10.1214/ss/1177011136
  17. Geweke J, Bayesian Statistics, 169 (1992)
  18. Goethals K, Journal of Agricultural Biological and Environmental Statistics, 26, 769 (2009)
  19. Goggins William B., Finkelstein Dianne M., A Proportional Hazards Model for Multivariate Interval-Censored Failure Time Data, 10.1111/j.0006-341x.2000.00940.x
  20. Heidelberger Philip, Welch Peter D., Simulation Run Length Control in the Presence of an Initial Transient, 10.1287/opre.31.6.1109
  21. Henschel Volkmar, Engel Jutta, Hölzel Dieter, Mansmann Ulrich, A semiparametric Bayesian proportional hazards model for interval censored data with frailty effects, 10.1186/1471-2288-9-9
  22. HOUGAARD PHILIP, Life table methods for heterogeneous populations: Distributions describing the heterogeneity, 10.1093/biomet/71.1.75
  23. HOUGAARD PHILIP, Survival models for heterogeneous populations derived from stable distributions, 10.1093/biomet/73.2.387
  24. Hougaard Philip, Analysis of Multivariate Survival Data, ISBN:9781461270874, 10.1007/978-1-4612-1304-8
  25. Jullion Astrid, Lambert Philippe, Robust specification of the roughness penalty prior distribution in spatially adaptive Bayesian P-splines models, 10.1016/j.csda.2006.09.027
  26. Kim Mimi Y., Xue Xiaonan, The analysis of multivariate interval-censored survival data, 10.1002/sim.1265
  27. Klein John P., Moeschberger M., Li Y. H., Wang S. T., Flournoy Nancy, Estimating Random Effects In the Framingham Heart Study, Survival Analysis: State of the Art (1992) ISBN:9789048141333 p.99-120, 10.1007/978-94-015-7983-4_7
  28. Komárek A, Statistica Sinica, 17, 549 (2007)
  29. KomÁrek Arnošt, Lesaffre Emmanuel, Bayesian Accelerated Failure Time Model With Multivariate Doubly Interval-Censored Data and Flexible Distributional Assumptions, 10.1198/016214507000000563
  30. Komárek Arnošt, Lesaffre Emmanuel, Hilton Joan F, Accelerated Failure Time Model for Arbitrarily Censored Data With Smoothed Error Distribution, 10.1198/106186005x63734
  31. Kor Chew-Teng, Cheng Kuang-Fu, Chen Yi-Hau, A method for analyzing clustered interval-censored data based on Cox's model, 10.1002/sim.5562
  32. Lam KF, Statistics in Medicine, 29, 680 (2010)
  33. Lambert Philippe, Archimedean copula estimation using Bayesian splines smoothing techniques, 10.1016/j.csda.2007.01.018
  34. Lambert Philippe, Nonparametric additive location-scale models for interval censored data, 10.1007/s11222-011-9292-6
  35. Lambert Philippe, Eilers Paul H. C., Bayesian proportional hazards model with time-varying regression coefficients: a penalized Poisson regression approach, 10.1002/sim.2396
  36. Lambert Philippe, Eilers Paul H.C., Bayesian density estimation from grouped continuous data, 10.1016/j.csda.2008.11.022
  37. Lang Stefan, Brezger Andreas, Bayesian P-Splines, 10.1198/1061860043010
  38. Leroy Roos, Bogaerts Kris, Lesaffre Emmanuel, Declerck Dominique, The emergence of permanent teeth in Flemish children, 10.1034/j.1600-0528.2003.00023.x
  39. Lesaffre Emmanuel, Komárek Arnošt, Declerck Dominique, An overview of methods for interval-censored data with an emphasis on applications in dentistry, 10.1191/0962280205sm417oa
  40. Peto R, Journal of the Royal Statistical Society (Series C), 22, 86 (1973)
  41. Roberts Gareth O., Rosenthal Jeffrey S., Optimal scaling for various Metropolis-Hastings algorithms, 10.1214/ss/1015346320
  42. Scheipl Fabian, Kneib Thomas, Locally adaptive Bayesian P-splines with a Normal-Exponential-Gamma prior, 10.1016/j.csda.2009.03.009
  43. Shih Joanna H., Louis Thomas A., Assessing gamma frailty models for clustered failure time data, 10.1007/bf00985771
  44. Strasak Alexander M., Lang Stefan, Kneib Thomas, Brant Larry J., Klenk Jochen, Hilbe Wolfgang, Oberaigner Willi, Ruttmann Elfriede, Kaltenbach Lalit, Concin Hans, Diem Günter, Pfeiffer Karl P., Ulmer Hanno, Use of Penalized Splines in Extended Cox-Type Additive Hazard Regression to Flexibly Estimate the Effect of Time-varying Serum Uric Acid on Risk of Cancer Incidence: A Prospective, Population-Based Study in 78,850 Men, 10.1016/j.annepidem.2008.08.009
  45. Therneau T, R package version 2.36–14 (2012)
  46. Turnbull BW, Journal of the Royal Statistical Society, Series B (Methodological), 38, 290 (1976)
  47. Vanobbergen J, European Journal of Paediatric Dentistry, 2, 87 (2000)
  48. Vaupel James W., Manton Kenneth G., Stallard Eric, The Impact of Heterogeneity in Individual Frailty on the Dynamics of Mortality, 10.2307/2061224
  49. Vaupel JW, The deviant dynamics of death in heterogeneous populations (1983)
  50. Wen CC, Statistica Sinica, 16, 439 (2013)
  51. Wienke Andreas, Frailty Models in Survival Analysis, ISBN:9781420073881, 10.1201/9781420073911
  52. Zhang Min, Davidian Marie, “Smooth” Semiparametric Regression Analysis for Arbitrarily Censored Time-to-Event Data, 10.1111/j.1541-0420.2007.00928.x
  53. Zuma Khangelani, A Bayesian Analysis of Correlated Interval-Censored Data, 10.1080/03610920601033710
  54. Zuma K, Journal of Data Science, 3, 241 (2005)