Literature DB >> 12704605

Dimension reduction and graphical exploration in regression including survival analysis.

R Dennis Cook1.   

Abstract

Recent advances in dimension reduction and visualization can greatly facilitate the exploratory and diagnostic stages of a regression analysis. This paper contains an expository discussion of selected methodology that came from these advances. Various applications are described, including new results on survival regressions with censoring. All of the methodology described in this paper is available in Arc, a recently released computer program that integrates many standard regression methods with recent developments in regression graphics. Arc implementations are indicated throughout the discussion. Copyright 2003 John Wiley & Sons, Ltd.

Mesh:

Year:  2003        PMID: 12704605     DOI: 10.1002/sim.1503

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


  3 in total

1.  Model-free predictor tests in survival regression through sufficient dimension reduction.

Authors:  Jae Keun Yoo; Keunbaik Lee
Journal:  Lifetime Data Anal       Date:  2010-11-04       Impact factor: 1.588

2.  Sufficient dimension reduction for censored regressions.

Authors:  Wenbin Lu; Lexin Li
Journal:  Biometrics       Date:  2010-09-28       Impact factor: 2.571

3.  Analysis of microarray right-censored data through fused sliced inverse regression.

Authors:  Jae Keun Yoo
Journal:  Sci Rep       Date:  2019-10-22       Impact factor: 4.379

  3 in total

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