Outlier detection method in GEEs

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F14%3A00222865" target="_blank" >RIV/68407700:21340/14:00222865 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1002/bimj.201300149" target="_blank" >http://dx.doi.org/10.1002/bimj.201300149</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/bimj.201300149" target="_blank" >10.1002/bimj.201300149</a>

Result language

angličtina

Original language name

Outlier detection method in GEEs

Original language description

The generalized estimating equations (GEEs) method has become quite useful in modeling correlated data. However, diagnostic tools to check that the selected final model fits the data as accurately as possible have not been explored intensively. In this paper, an outlier detection technique is developed based on the use of the ?working? score test statistic to test an appropriate mean-shift model in the context of longitudinal studies based on GEEs. Through a simulation study it has been shown that thismethod correctly singled out the outlier when the data set had a known outlier. The method is applied to a set of data to illustrate the outlier detection procedure in GEEs.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2014

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Biometrical Journal

ISSN

0323-3847

e-ISSN

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Volume of the periodical

56

Issue of the periodical within the volume

5

Country of publishing house

DE - GERMANY

Number of pages

13

Pages from-to

838-850

UT code for WoS article

000341705400018

EID of the result in the Scopus database

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