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Cited by 13,847

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Simultaneous Inference in General Parametric Models

Open access
Hothorn, Torsten, Bretz, Frank, Westfall, Peter·2008·Biometrical Journal
DOI 10.1002/bimj.200810425
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Abstract

Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre‐specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add‐on package multcomp, which provides a convenient interface to the general approach adopted here. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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Research works printed but not linked: 24

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Metadata

Authors
Hothorn, T., Bretz, F., & Westfall, P.
Venue
Biometrical Journal
Publisher
Wiley
Published
2008-06
Volume
50
Issue
3
Pages
346-363
ISSN
  • 0323-3847 (ISSN-L)
  • 1521-4036
DOI
10.1002/bimj.200810425
OpenAlex
W2159267296
Cited by
13,847
References
1
FWCI
78.23
Type
journal article
Language
en
Open access
green
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)

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