138 related articles for article (PubMed ID: 27078815)
1. A sup-score test for the cure fraction in mixture models for long-term survivors.
Hsu WW; Todem D; Kim K
Biometrics; 2016 Dec; 72(4):1348-1357. PubMed ID: 27078815
[TBL] [Abstract][Full Text] [Related]
2. A quasi-score statistic for homogeneity testing against covariate-varying heterogeneity.
Todem D; Hsu WW; Fine JP
Scand Stat Theory Appl; 2018 Sep; 45(3):465-481. PubMed ID: 30275656
[TBL] [Abstract][Full Text] [Related]
3. Nonparametric covariate hypothesis tests for the cure rate in mixture cure models.
López-Cheda A; Jácome MA; Van Keilegom I; Cao R
Stat Med; 2020 Jul; 39(17):2291-2307. PubMed ID: 32478440
[TBL] [Abstract][Full Text] [Related]
4. A score-type test for heterogeneity in zero-inflated models in a stratified population.
Cao G; Hsu WW; Todem D
Stat Med; 2014 May; 33(12):2103-14. PubMed ID: 24488881
[TBL] [Abstract][Full Text] [Related]
5. Cure fraction estimation from the mixture cure models for grouped survival data.
Yu B; Tiwari RC; Cronin KA; Feuer EJ
Stat Med; 2004 Jun; 23(11):1733-47. PubMed ID: 15160405
[TBL] [Abstract][Full Text] [Related]
6. Nonparametric scanning tests of homogeneity for hierarchical models with continuous covariates.
Todem D; Hsu WW; Kim K
Biometrics; 2023 Sep; 79(3):2063-2075. PubMed ID: 36454666
[TBL] [Abstract][Full Text] [Related]
7. A Case Study Examining the Usefulness of Cure Modelling for the Prediction of Survival Based on Data Maturity.
Grant TS; Burns D; Kiff C; Lee D
Pharmacoeconomics; 2020 Apr; 38(4):385-395. PubMed ID: 31848900
[TBL] [Abstract][Full Text] [Related]
8. Current estimates of the cure fraction: a feasibility study of statistical cure for breast and colorectal cancer.
Stedman MR; Feuer EJ; Mariotto AB
J Natl Cancer Inst Monogr; 2014 Nov; 2014(49):244-54. PubMed ID: 25417238
[TBL] [Abstract][Full Text] [Related]
9. Estimating the proportion cured of cancer: some practical advice for users.
Yu XQ; De Angelis R; Andersson TM; Lambert PC; O'Connell DL; Dickman PW
Cancer Epidemiol; 2013 Dec; 37(6):836-42. PubMed ID: 24042025
[TBL] [Abstract][Full Text] [Related]
10. Goodness-of-fit test for a parametric mixture cure model with partly interval-censored data.
Geng Z; Li J; Niu Y; Wang X
Stat Med; 2023 Feb; 42(4):407-421. PubMed ID: 36477899
[TBL] [Abstract][Full Text] [Related]
11. Minimum follow-up time required for the estimation of statistical cure of cancer patients: verification using data from 42 cancer sites in the SEER database.
Tai P; Yu E; Cserni G; Vlastos G; Royce M; Kunkler I; Vinh-Hung V
BMC Cancer; 2005 May; 5():48. PubMed ID: 15904508
[TBL] [Abstract][Full Text] [Related]
12. On the efficiency of score tests for homogeneity in two-component parametric models for discrete data.
Todem D; Hsu WW; Kim K
Biometrics; 2012 Sep; 68(3):975-82. PubMed ID: 22348298
[TBL] [Abstract][Full Text] [Related]
13. Semiparametric accelerated failure time cure rate mixture models with competing risks.
Choi S; Zhu L; Huang X
Stat Med; 2018 Jan; 37(1):48-59. PubMed ID: 28983935
[TBL] [Abstract][Full Text] [Related]
14. Improved survival time: what can survival cure models tell us about population-based survival improvements in late-stage colorectal, ovarian, and testicular cancer?
Huang L; Cronin KA; Johnson KA; Mariotto AB; Feuer EJ
Cancer; 2008 May; 112(10):2289-300. PubMed ID: 18393325
[TBL] [Abstract][Full Text] [Related]
15. Estimating Long-Term Survival for Patients with Relapsed or Refractory Large B-Cell Lymphoma Treated with Chimeric Antigen Receptor Therapy: A Comparison of Standard and Mixture Cure Models.
Bansal A; Sullivan SD; Lin VW; Purdum AG; Navale L; Cheng P; Ramsey SD
Med Decis Making; 2019 Apr; 39(3):294-298. PubMed ID: 30819038
[TBL] [Abstract][Full Text] [Related]
16. A new estimation method for the semiparametric accelerated failure time mixture cure model.
Zhang J; Peng Y
Stat Med; 2007 Jul; 26(16):3157-71. PubMed ID: 17094075
[TBL] [Abstract][Full Text] [Related]
17. RECeUS: Ratio estimation of censored uncured subjects, a different approach for assessing cure model appropriateness in studies with long-term survivors.
Selukar S; Othus M
Stat Med; 2023 Feb; 42(3):209-227. PubMed ID: 36433635
[TBL] [Abstract][Full Text] [Related]
18. Characteristics of Long-Term Survivors of Epithelial Ovarian Cancer.
Cress RD; Chen YS; Morris CR; Petersen M; Leiserowitz GS
Obstet Gynecol; 2015 Sep; 126(3):491-497. PubMed ID: 26244529
[TBL] [Abstract][Full Text] [Related]
19. Promoting structural effects of covariates in the cure rate model with penalization.
Fan X; Liu M; Fang K; Huang Y; Ma S
Stat Methods Med Res; 2017 Oct; 26(5):2078-2092. PubMed ID: 28480830
[TBL] [Abstract][Full Text] [Related]
20. Methodology to predict long-term cancer survival from short-term data using Tobacco Cancer Risk and Absolute Cancer Cure models.
Mould RF; Lederman M; Tai P; Wong JK
Phys Med Biol; 2002 Nov; 47(22):3893-924. PubMed ID: 12476973
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
