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Items: 1 to 20 of 96

1.

An early- and late-stage convolution model for disease natural history.

Pinsky PF.

Biometrics. 2004 Mar;60(1):191-8.

PMID:
15032789
2.

Estimation of sojourn time in chronic disease screening without data on interval cases.

Chen TH, Kuo HS, Yen MF, Lai MS, Tabar L, Duffy SW.

Biometrics. 2000 Mar;56(1):167-72.

PMID:
10783792
4.
5.

Two-stage models for the analysis of cancer screening data.

Brookmeyer R, Day NE.

Biometrics. 1987 Sep;43(3):657-69.

PMID:
3663822
6.

Case-control studies for estimation of the natural history of preclinical disease from screening data.

Brookmeyer R, Day NE, Moss S.

Stat Med. 1986 Mar-Apr;5(2):127-38.

PMID:
3715256
7.

Effect of length biased sampling of unobserved sojourn times on the survival distribution when disease is screen detected.

Kafadar K, Prorok PC.

Stat Med. 2009 Jul 20;28(16):2116-46. doi: 10.1002/sim.3601.

PMID:
19424959
8.
9.

Cost-effectiveness analysis of screening for lung cancer with low dose spiral CT (computed tomography) in the Australian setting.

Manser R, Dalton A, Carter R, Byrnes G, Elwood M, Campbell DA.

Lung Cancer. 2005 May;48(2):171-85.

PMID:
15829317
10.
11.

Estimation and prediction system for multi-state disease process: application to analysis of organized screening regime.

Chang CM, Lin WC, Kuo HS, Yen MF, Chen TH.

J Eval Clin Pract. 2007 Dec;13(6):867-81.

PMID:
18070257
12.

Reducing the effects of lead-time bias, length bias and over-detection in evaluating screening mammography: a censored bivariate data approach.

Mahnken JD, Chan W, Freeman DH Jr, Freeman JL.

Stat Methods Med Res. 2008 Dec;17(6):643-63. doi: 10.1177/0962280207087309. Review.

PMID:
18445697
13.

Reducing ovarian cancer mortality through screening: Is it possible, and can we afford it?

Havrilesky LJ, Sanders GD, Kulasingam S, Myers ER.

Gynecol Oncol. 2008 Nov;111(2):179-87. doi: 10.1016/j.ygyno.2008.07.006.

PMID:
18722004
14.

Progression rates of colorectal cancer by Dukes' stage in a high-risk group: analysis of selective colorectal cancer screening.

Wong JM, Yen MF, Lai MS, Duffy SW, Smith RA, Chen TH.

Cancer J. 2004 May-Jun;10(3):160-9.

PMID:
15285925
15.
16.

Evaluation of screening for nasopharyngeal carcinoma: trial design using Markov chain models.

Chen HH, Prevost TC, Duffy SW.

Br J Cancer. 1999 Apr;79(11-12):1894-900.

17.

A natural history model of stage progression applied to breast cancer.

Plevritis SK, Salzman P, Sigal BM, Glynn PW.

Stat Med. 2007 Feb 10;26(3):581-95.

PMID:
16598706
18.

Estimation of post-lead-time survival under dependence between lead-time and post-lead-time survival.

Xu JL, Fagerstrom RM, Prorok PC.

Stat Med. 1999 Jan 30;18(2):155-62.

PMID:
10028136
19.

ORDMKV: a computer program fitting proportional odds model for multi-state Markov process.

Guo W, Marshall G.

Comput Methods Programs Biomed. 1995 Apr;46(3):257-63.

PMID:
7656559
20.

Estimating mean sojourn time and screening sensitivity using questionnaire data on time since previous screening.

Weedon-Fekjaer H, Lindqvist BH, Vatten LJ, Aalen OO, Tretli S.

J Med Screen. 2008;15(2):83-90. doi: 10.1258/jms.2008.007071.

PMID:
18573776
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