Literature DB >> 19697291

A score test for assessing the cured proportion in the long-term survivor mixture model.

Yun Zhao1, Andy H Lee, Kelvin K W Yau, Valerie Burke, Geoffrey J McLachlan.   

Abstract

The long-term survivor mixture model is commonly applied to analyse survival data when some individuals may never experience the failure event of interest. A score test is presented to assess whether the cured proportion is significant to justify the long-term survivor mixture model. Sampling distribution and power of the test statistic are evaluated by simulation studies. The results confirm that the proposed test statistic performs well in finite sample situations. The test procedure is illustrated using a breast cancer survival data set and the clustered multivariate failure times from a multi-centre clinical trial of carcinoma.

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Year:  2009        PMID: 19697291      PMCID: PMC2885914          DOI: 10.1002/sim.3696

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  7 in total

1.  A nonparametric mixture model for cure rate estimation.

Authors:  Y Peng; K B Dear
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

2.  Estimation in a Cox proportional hazards cure model.

Authors:  J P Sy; J M Taylor
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

3.  Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma.

Authors:  K K Yau; A S Ng
Journal:  Stat Med       Date:  2001-06-15       Impact factor: 2.373

4.  Modelling the distribution of ischaemic stroke-specific survival time using an EM-based mixture approach with random effects adjustment.

Authors:  S K Ng; G J McLachlan; Kelvin K W Yau; Andy H Lee
Journal:  Stat Med       Date:  2004-09-15       Impact factor: 2.373

5.  A score test for zero-inflation in correlated count data.

Authors:  Liming Xiang; Andy H Lee; Kelvin K W Yau; Geoffrey J McLachlan
Journal:  Stat Med       Date:  2006-05-30       Impact factor: 2.373

6.  A score test for overdispersion in zero-inflated poisson mixed regression model.

Authors:  Liming Xiang; Andy H Lee; Kelvin K W Yau; Geoffrey J McLachlan
Journal:  Stat Med       Date:  2007-03-30       Impact factor: 2.373

7.  Predictive value of lectin binding on breast-cancer recurrence and survival.

Authors:  A J Leathem; S A Brooks
Journal:  Lancet       Date:  1987-05-09       Impact factor: 79.321

  7 in total
  2 in total

1.  A sup-score test for the cure fraction in mixture models for long-term survivors.

Authors:  Wei-Wen Hsu; David Todem; KyungMann Kim
Journal:  Biometrics       Date:  2016-04-14       Impact factor: 2.571

2.  Is there a subgroup of long-term evolution among patients with advanced lung cancer?: hints from the analysis of survival curves from cancer registry data.

Authors:  Lizet Sanchez; Patricia Lorenzo-Luaces; Carmen Viada; Yaima Galan; Javier Ballesteros; Tania Crombet; Agustin Lage
Journal:  BMC Cancer       Date:  2014-12-11       Impact factor: 4.430

  2 in total

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