Literature DB >> 7820292

On the role of finite mixture models in survival analysis.

G J McLachlan1, D C McGiffin.   

Abstract

In this paper we review the role of finite mixture models in the field of survival analysis. Finite mixture models can be used to analyse failure-time data in a variety of situations. In particular, they provide a way of modelling time to failure in the case of competing risks.

Mesh：

Year:  1994        PMID： 7820292     DOI： 10.1177/096228029400300302

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN： 0962-2802            Impact factor:   3.021


  4 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.  Modeling Heterogeneity in Healthcare Utilization Using Massive Medical Claims Data.

Authors:  Ross P Hilton; Yuchen Zheng; Nicoleta Serban
Journal:  J Am Stat Assoc       Date:  2017-06-26       Impact factor: 5.033

3.  Mixture distributions in multi-state modelling: some considerations in a study of psoriatic arthritis.

Authors:  Aidan G O'Keeffe; Brian D M Tom; Vernon T Farewell
Journal:  Stat Med       Date:  2012-07-26       Impact factor: 2.373

4.  Comparing a Query Compound with Drug Target Classes Using 3D-Chemical Similarity.

Authors:  Sang-Hyeok Lee; Sangjin Ahn; Mi-Hyun Kim
Journal:  Int J Mol Sci       Date:  2020-06-12       Impact factor: 5.923
  4 in total

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