Literature DB >> 10378260

Mixtures of proportional hazards regression models.

O Rosen1, M Tanner.   

Abstract

This paper presents a mixture model which combines features of the usual Cox proportional hazards model with those of a class of models, known as mixtures-of-experts. The resulting model is more flexible than the usual Cox model in the sense that the log hazard ratio is allowed to vary non-linearly as a function of the covariates. Thus it provides a flexible approach to both modelling survival data and model checking. The method is illustrated with simulated data, as well as with multiple myeloma data.

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Year:  1999        PMID: 10378260     DOI: 10.1002/(sici)1097-0258(19990515)18:9<1119::aid-sim116>3.0.co;2-v

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


  3 in total

1.  An Exponential Tilt Mixture Model for Time-to-Event Data to Evaluate Treatment Effect Heterogeneity in Randomized Clinical Trials.

Authors:  Chi Wang; Zhiqiang Tan; Thomas A Louis
Journal:  Biom Biostat Int J       Date:  2014-09-17

2.  Infinite mixture-of-experts model for sparse survival regression with application to breast cancer.

Authors:  Sudhir Raman; Thomas J Fuchs; Peter J Wild; Edgar Dahl; Joachim M Buhmann; Volker Roth
Journal:  BMC Bioinformatics       Date:  2010-10-26       Impact factor: 3.169

3.  An Integrated Framework for Reducing Hospital Readmissions using Risk Trajectories Characterization and Discharge Timing Optimization.

Authors:  Adel Alaeddini; Jonathan E Helm; Pengyi Shi; Syed Hasib Akhter Faruqui
Journal:  IISE Trans Healthc Syst Eng       Date:  2019-04-19
  3 in total

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