Literature DB >> 19051394

Asymptotic distribution of score statistics for spatial cluster detection with censored data.

Daniel Commenges1, Benoit Liquet.   

Abstract

SUMMARY: Cook, Gold, and Li (2007, Biometrics 63, 540-549) extended the Kulldorff (1997, Communications in Statistics 26, 1481-1496) scan statistic for spatial cluster detection to survival-type observations. Their approach was based on the score statistic and they proposed a permutation distribution for the maximum of score tests. The score statistic makes it possible to apply the scan statistic idea to models including explanatory variables. However, we show that the permutation distribution requires strong assumptions of independence between potential cluster and both censoring and explanatory variables. In contrast, we present an approach using the asymptotic distribution of the maximum of score statistics in a manner not requiring these assumptions.

Mesh:

Year:  2008        PMID: 19051394     DOI: 10.1111/j.1541-0420.2008.01132_1.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  3 in total

1.  Rejoinder to ``Asymptotic Distribution of Score Statistics for Spatial Cluster Detection with Censored Data"

Authors:  Andrea J Cook; Yi Li
Journal:  Biometrics       Date:  2008-12       Impact factor: 2.571

2.  CPMCGLM: an R package for p-value adjustment when looking for an optimal transformation of a single explanatory variable in generalized linear models.

Authors:  Benoit Liquet; Jérémie Riou
Journal:  BMC Med Res Methodol       Date:  2019-04-16       Impact factor: 4.615

3.  Correction of the significance level when attempting multiple transformations of an explanatory variable in generalized linear models.

Authors:  Benoit Liquet; Jérémie Riou
Journal:  BMC Med Res Methodol       Date:  2013-06-08       Impact factor: 4.615

  3 in total

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