Classical and a robust method in dealing with outlier in factorial designs : an empirical example.

Valid analysis of an experimental design data requires several assumptions, such as normality, constant variances and independency. In practice, those assumptions can be violated due to causes, such as the presence of an outlying observation. A more appropriate and modern approach is needed, that...

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Main Authors: Fitrianto, Anwar, Midi, Habshah
Format: Conference or Workshop Item
Language:English
English
Published: 2012
Online Access:http://psasir.upm.edu.my/id/eprint/27587/
http://psasir.upm.edu.my/id/eprint/27587/1/ID%2027587.pdf
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author Fitrianto, Anwar
Midi, Habshah
author_facet Fitrianto, Anwar
Midi, Habshah
author_sort Fitrianto, Anwar
building UPM Institutional Repository
collection Online Access
description Valid analysis of an experimental design data requires several assumptions, such as normality, constant variances and independency. In practice, those assumptions can be violated due to causes, such as the presence of an outlying observation. A more appropriate and modern approach is needed, that is to use a robust procedure that provides estimation, inference and testing that are not influenced by outlying observations but describes correctly the structure for the bulk of the data. A well-known approach to handle dataset with outliers is the M-estimation. In this paper, both classical and robust procedures are employed to data of a factorial experiment. And we point out that relying on classical method instead of robust methods lead to misleading conclusion of the analysis.
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institution Universiti Putra Malaysia
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language English
English
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publishDate 2012
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spelling upm-275872014-06-13T08:09:13Z http://psasir.upm.edu.my/id/eprint/27587/ Classical and a robust method in dealing with outlier in factorial designs : an empirical example. Fitrianto, Anwar Midi, Habshah Valid analysis of an experimental design data requires several assumptions, such as normality, constant variances and independency. In practice, those assumptions can be violated due to causes, such as the presence of an outlying observation. A more appropriate and modern approach is needed, that is to use a robust procedure that provides estimation, inference and testing that are not influenced by outlying observations but describes correctly the structure for the bulk of the data. A well-known approach to handle dataset with outliers is the M-estimation. In this paper, both classical and robust procedures are employed to data of a factorial experiment. And we point out that relying on classical method instead of robust methods lead to misleading conclusion of the analysis. 2012 Conference or Workshop Item NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/27587/1/ID%2027587.pdf Fitrianto, Anwar and Midi, Habshah (2012) Classical and a robust method in dealing with outlier in factorial designs : an empirical example. In: 2nd Basic Science International Conference, 24-25 Feb. 2012, Indonesia. . English
spellingShingle Fitrianto, Anwar
Midi, Habshah
Classical and a robust method in dealing with outlier in factorial designs : an empirical example.
title Classical and a robust method in dealing with outlier in factorial designs : an empirical example.
title_full Classical and a robust method in dealing with outlier in factorial designs : an empirical example.
title_fullStr Classical and a robust method in dealing with outlier in factorial designs : an empirical example.
title_full_unstemmed Classical and a robust method in dealing with outlier in factorial designs : an empirical example.
title_short Classical and a robust method in dealing with outlier in factorial designs : an empirical example.
title_sort classical and a robust method in dealing with outlier in factorial designs : an empirical example.
url http://psasir.upm.edu.my/id/eprint/27587/
http://psasir.upm.edu.my/id/eprint/27587/1/ID%2027587.pdf