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Items: 1 to 20 of 130

1.

Estimating a time-dependent concordance index for survival prediction models with covariate dependent censoring.

Gerds TA, Kattan MW, Schumacher M, Yu C.

Stat Med. 2013 Jun 15;32(13):2173-84. doi: 10.1002/sim.5681. Epub 2012 Nov 22.

PMID:
23172755
2.

Analysis of accelerated failure time data with dependent censoring using auxiliary variables via nonparametric multiple imputation.

Hsu CH, Taylor JM, Hu C.

Stat Med. 2015 Aug 30;34(19):2768-80. doi: 10.1002/sim.6534. Epub 2015 May 21.

3.

Cause-specific cumulative incidence estimation and the fine and gray model under both left truncation and right censoring.

Geskus RB.

Biometrics. 2011 Mar;67(1):39-49. doi: 10.1111/j.1541-0420.2010.01420.x.

PMID:
20377575
5.

Double inverse-weighted estimation of cumulative treatment effects under nonproportional hazards and dependent censoring.

Schaubel DE, Wei G.

Biometrics. 2011 Mar;67(1):29-38. doi: 10.1111/j.1541-0420.2010.01449.x.

6.

Survival curve estimation with dependent left truncated data using Cox's model.

Mackenzie T.

Int J Biostat. 2012 Oct 19;8(1). pii: /j/ijb.2012.8.issue-1/1557-4679.1312/1557-4679.1312.xml. doi: 10.1515/1557-4679.1312.

PMID:
23104845
7.

Presence or absence of a positive pathological margin outperforms any other margin-associated variable in predicting clinically relevant biochemical recurrence in Gleason 7 prostate cancer.

Huang JG, Pedersen J, Hong MK, Harewood LM, Peters J, Costello AJ, Hovens CM, Corcoran NM.

BJU Int. 2013 May;111(6):921-7. doi: 10.1111/j.1464-410X.2012.11665.x. Epub 2013 Jan 25.

8.

Naive Bayesian-based nomogram for prediction of prostate cancer recurrence.

Demsar J, Zupan B, Kattan MW, Beck JR, Bratko I.

Stud Health Technol Inform. 1999;68:436-41.

PMID:
10724923
9.

Partly conditional survival models for longitudinal data.

Zheng Y, Heagerty PJ.

Biometrics. 2005 Jun;61(2):379-91.

PMID:
16011684
11.

Estimation of colorectal adenoma recurrence with dependent censoring.

Hsu CH, Long Q, Alberts DS.

BMC Med Res Methodol. 2009 Sep 29;9:66. doi: 10.1186/1471-2288-9-66.

12.
13.
14.

miR-21 as an independent biochemical recurrence predictor and potential therapeutic target for prostate cancer.

Li T, Li RS, Li YH, Zhong S, Chen YY, Zhang CM, Hu MM, Shen ZJ.

J Urol. 2012 Apr;187(4):1466-72. doi: 10.1016/j.juro.2011.11.082. Epub 2012 Feb 17.

PMID:
22341810
15.

Estimating lifetime or episode-of-illness costs under censoring.

Basu A, Manning WG.

Health Econ. 2010 Sep;19(9):1010-28. doi: 10.1002/hec.1640. Erratum in: Health Econ. 2011 Jan;20(1):125-6.

PMID:
20665908
16.

Evaluation of ki-67 staining levels as an independent biomarker of biochemical recurrence after salvage radiation therapy for prostate cancer.

Parker AS, Heckman MG, Wu KJ, Crook JE, Hilton TW, Pisansky TM, Bernard JR, Schild SE, Khor LY, Hammond EH, Pollack A, Buskirk SJ.

Int J Radiat Oncol Biol Phys. 2009 Dec 1;75(5):1364-70. doi: 10.1016/j.ijrobp.2008.12.061. Epub 2009 May 21.

PMID:
19464826
17.

Joint models for efficient estimation in proportional hazards regression models.

Slasor P, Laird N.

Stat Med. 2003 Jul 15;22(13):2137-48.

PMID:
12820279
18.

Estimating the concordance probability in a survival analysis with a discrete number of risk groups.

Heller G, Mo Q.

Lifetime Data Anal. 2016 Apr;22(2):263-79. doi: 10.1007/s10985-015-9330-3. Epub 2015 May 29.

19.

Estimation of prediction error for survival models.

Lawless JF, Yuan Y.

Stat Med. 2010 Jan 30;29(2):262-74. doi: 10.1002/sim.3758.

PMID:
19882678
20.

Concordance for prognostic models with competing risks.

Wolbers M, Blanche P, Koller MT, Witteman JC, Gerds TA.

Biostatistics. 2014 Jul;15(3):526-39. doi: 10.1093/biostatistics/kxt059. Epub 2014 Feb 2.

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