225 related articles for article (PubMed ID: 12436466)
21. A frailty model approach for regression analysis of multivariate current status data.
Chen MH; Tong X; Sun J
Stat Med; 2009 Nov; 28(27):3424-36. PubMed ID: 19739240
[TBL] [Abstract][Full Text] [Related]
22. Sample size determination for comparing several survival curves with unequal allocations.
Halabi S; Singh B
Stat Med; 2004 Jun; 23(11):1793-815. PubMed ID: 15160409
[TBL] [Abstract][Full Text] [Related]
23. A Monte Carlo approach for change-point detection in the Cox proportional hazards model.
Liu M; Lu W; Shao Y
Stat Med; 2008 Aug; 27(19):3894-909. PubMed ID: 18254131
[TBL] [Abstract][Full Text] [Related]
24. Regression analysis of multivariate grouped survival data.
Guo SW; Lin DY
Biometrics; 1994 Sep; 50(3):632-9. PubMed ID: 7981390
[TBL] [Abstract][Full Text] [Related]
25. Semiparametric analysis of survival data with left truncation and dependent right censoring.
Jiang H; Fine JP; Chappell R
Biometrics; 2005 Jun; 61(2):567-75. PubMed ID: 16011706
[TBL] [Abstract][Full Text] [Related]
26. Bootstrap analysis of multivariate failure time data.
Monaco J; Cai J; Grizzle J
Stat Med; 2005 Nov; 24(22):3387-400. PubMed ID: 16237657
[TBL] [Abstract][Full Text] [Related]
27. A method for sequential analysis of survival data with nonproportional hazards.
Sooriyarachchi MR; Whitehead J
Biometrics; 1998 Sep; 54(3):1072-84. PubMed ID: 9750253
[TBL] [Abstract][Full Text] [Related]
28. Performance of statistical methods for analysing survival data in the presence of non-random compliance.
Odondi L; McNamee R
Stat Med; 2010 Dec; 29(29):2994-3003. PubMed ID: 20963732
[TBL] [Abstract][Full Text] [Related]
29. Simple adjustments for randomized trials with nonrandomly missing or censored outcomes arising from informative covariates.
Baker SG; Fitzmaurice GM; Freedman LS; Kramer BS
Biostatistics; 2006 Jan; 7(1):29-40. PubMed ID: 15923407
[TBL] [Abstract][Full Text] [Related]
30. Cure rate model with interval censored data.
Kim YJ; Jhun M
Stat Med; 2008 Jan; 27(1):3-14. PubMed ID: 17516589
[TBL] [Abstract][Full Text] [Related]
31. Analyses of cumulative incidence functions via non-parametric multiple imputation.
Ruan PK; Gray RJ
Stat Med; 2008 Nov; 27(27):5709-24. PubMed ID: 18712779
[TBL] [Abstract][Full Text] [Related]
32. Non-parametric estimation and model checking procedures for marginal gap time distributions for recurrent events.
Kvist K; Gerster M; Andersen PK; Kessing LV
Stat Med; 2007 Dec; 26(30):5394-410. PubMed ID: 17994608
[TBL] [Abstract][Full Text] [Related]
33. Multiple imputation to estimate the association between eyes in disease progression with interval-censored data.
Glynn RJ; Rosner B
Stat Med; 2004 Nov; 23(21):3307-18. PubMed ID: 15493063
[TBL] [Abstract][Full Text] [Related]
34. A simple test for independent censoring under the proportional hazards model.
Lee SY; Wolfe RA
Biometrics; 1998 Sep; 54(3):1176-82. PubMed ID: 9840972
[TBL] [Abstract][Full Text] [Related]
35. Analyzing doubly censored data with covariates, with application to AIDS.
Kim MY; De Gruttola VG; Lagakos SW
Biometrics; 1993 Mar; 49(1):13-22. PubMed ID: 8513098
[TBL] [Abstract][Full Text] [Related]
36. Accelerated failure time models with covariates subject to measurement error.
He W; Yi GY; Xiong J
Stat Med; 2007 Nov; 26(26):4817-32. PubMed ID: 17436310
[TBL] [Abstract][Full Text] [Related]
37. Administrative and artificial censoring in censored regression models.
Joffe MM
Stat Med; 2001 Aug; 20(15):2287-304. PubMed ID: 11468764
[TBL] [Abstract][Full Text] [Related]
38. A robust method for proportional hazards regression.
Minder CE; Bednarski T
Stat Med; 1996 May; 15(10):1033-47. PubMed ID: 8783440
[TBL] [Abstract][Full Text] [Related]
39. Evaluation of long-term survival: use of diagnostics and robust estimators with Cox's proportional hazards model.
Valsecchi MG; Silvestri D; Sasieni P
Stat Med; 1996 Dec; 15(24):2763-80. PubMed ID: 8981685
[TBL] [Abstract][Full Text] [Related]
40. Estimation of treatment effect adjusting for dependent censoring using the IPCW method: an application to a large primary prevention study for coronary events (MEGA study).
Yoshida M; Matsuyama Y; Ohashi Y;
Clin Trials; 2007; 4(4):318-28. PubMed ID: 17848493
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
