This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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193
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Social Statistics Section
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Abstract - #306673 |
Title:
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A Monte Carlo Comparison of Robust MANOVA Test Statistics
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Author(s):
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Holmes Finch*+ and Brian French
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Companies:
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Ball State University and Washington State University
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Address:
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Department of Educational Psychology, Muncie, IN, 47306,
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Keywords:
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MANOVA ;
Robust tests ;
Monte Carlo
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Abstract:
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MANOVA is a popular statistical tool allowing for comparison of group mean vectors. MANOVA requires three assumptions: (a) normality of errors, (b) equality of group covariance matrices and (c) independence of errors. When these are violated, MANOVA performs poorly in terms of Type I error rate and power. Alternatives to the standard test statistic exist. However, a systematic simultaneous comparison has not been conducted. This simulation study compared Type I error rates and power of standard MANOVA tests with these alternatives in the presence and absence of assumption violations, across a variety of conditions. Results suggest that when assumptions were met, the standard test functioned well, but when assumptions were not met, it performed poorly, while several alternatives performed somewhat better. The presentation will include advice for selecting alternatives in practice.
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Authors who are presenting talks have a * after their name.
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