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Items: 1 to 20 of 23

1.

Estimating the crude probability of death due to cancer and other causes using relative survival models.

Lambert PC, Dickman PW, Nelson CP, Royston P.

Stat Med. 2010 Mar 30;29(7-8):885-95. doi: 10.1002/sim.3762.

PMID:
20213719
2.

Mortality among immigrants in England and Wales by major causes of death, 1971-2012: A longitudinal analysis of register-based data.

Wallace M, Kulu H.

Soc Sci Med. 2015 Dec;147:209-21. doi: 10.1016/j.socscimed.2015.10.060. Epub 2015 Nov 10. Erratum in: Soc Sci Med. 2016 Jan;148:59.

PMID:
26595089
3.

Estimating relative survival among people registered with cancer in England and Wales.

Reeves GK, Beral V, Bull D, Quinn M.

Br J Cancer. 1999 Jan;79(1):18-22. Review.

4.

Estimating the personal cure rate of cancer patients using population-based grouped cancer survival data.

Binbing Yu, Tiwari RC, Feuer EJ.

Stat Methods Med Res. 2011 Jun;20(3):261-74. doi: 10.1177/0962280209347046. Epub 2010 Feb 24.

5.

Spatial variation in prostate cancer survival in the Northern and Yorkshire region of England using Bayesian relative survival smoothing.

Fairley L, Forman D, West R, Manda S.

Br J Cancer. 2008 Dec 2;99(11):1786-93. doi: 10.1038/sj.bjc.6604757. Epub 2008 Nov 4.

6.

Estimating long-term crude probability of death among young breast cancer patients: a Bayesian approach.

Clèries R, Buxó M, Yasui Y, Marcos-Gragera R, Martínez JM, Ameijide A, Galceran J, Borràs JM, Izquierdo À.

Tumori. 2016 Dec 1;102(6):555-561. doi: 10.5301/tj.5000545. Epub 2016 Sep 20.

PMID:
27647229
7.

A measure of explained risk in the proportional hazards model.

Heller G.

Biostatistics. 2012 Apr;13(2):315-25. doi: 10.1093/biostatistics/kxr047. Epub 2011 Dec 21.

8.
9.

Survival and cause of death in a cohort of patients with parkinsonism: possible clues to aetiology?

Ben-Shlomo Y, Marmot MG.

J Neurol Neurosurg Psychiatry. 1995 Mar;58(3):293-9.

10.

Challenges in the estimation of Net SURvival: The CENSUR working survival group.

Giorgi R; CENSUR working survival group.

Rev Epidemiol Sante Publique. 2016 Oct;64(5):367-371. doi: 10.1016/j.respe.2016.05.005. Epub 2016 Oct 25.

PMID:
27793412
11.

Flexible parametric joint modelling of longitudinal and survival data.

Crowther MJ, Abrams KR, Lambert PC.

Stat Med. 2012 Dec 30;31(30):4456-71. doi: 10.1002/sim.5644. Epub 2012 Oct 4.

PMID:
23037571
12.

A class of transformation covariate regression models for estimating the excess hazard in relative survival analysis.

Yu B.

Am J Epidemiol. 2013 Apr 1;177(7):708-17. doi: 10.1093/aje/kws288. Epub 2013 Mar 13.

13.

Dynamic regression hazards models for relative survival.

Cortese G, Scheike TH.

Stat Med. 2008 Aug 15;27(18):3563-84. doi: 10.1002/sim.3242.

14.

Determining transition probabilities from mortality rates and autopsy findings.

Black WC, Nease RF Jr, Welch HG.

Med Decis Making. 1997 Jan-Mar;17(1):87-93.

PMID:
8994155
15.

Analysing population-based cancer survival - settling the controversies.

Pohar Perme M, Estève J, Rachet B.

BMC Cancer. 2016 Dec 3;16(1):933.

16.

Survival from prostate cancer in England and Wales up to 2001.

Clarke NW.

Br J Cancer. 2008 Sep 23;99 Suppl 1:S78-9. doi: 10.1038/sj.bjc.6604596. No abstract available.

17.

Fitting competing risks with an assumed copula.

Escarela G, Carrière JF.

Stat Methods Med Res. 2003 Aug;12(4):333-49.

PMID:
12939100
18.

Flexible parametric modelling of the cause-specific cumulative incidence function.

Lambert PC, Wilkes SR, Crowther MJ.

Stat Med. 2017 Apr 30;36(9):1429-1446. doi: 10.1002/sim.7208. Epub 2016 Dec 22.

PMID:
28008649
19.

Funnel plots for population-based cancer survival: principles, methods and applications.

Quaresma M, Coleman MP, Rachet B.

Stat Med. 2014 Mar 15;33(6):1070-80. doi: 10.1002/sim.5953. Epub 2013 Sep 4.

PMID:
24038332
20.

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.

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