This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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686
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 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 - #307427 |
Title:
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Sample Size Planning to Obtain Narrow Confidence Intervals for the RMSEA
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Author(s):
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Ken Kelley*+ and Keke Lai
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Companies:
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University of Notre Dame and University of Notre Dame
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Address:
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Mendoza College of Business, Notre Dame, IN, 46556,
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Keywords:
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sample size planning ;
structural equation modeling ;
research design ;
power analysis ;
accuracy in parameter estimation
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Abstract:
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The root mean square error of approximation (RMSEA) is the most widely used measure of model fit in structural equation modeling. When the RMSEA is of interest, so too should the accompanying confidence interval. A wide confidence interval illustrates the uncertainty with which a parameter has been estimated. The accuracy in parameter estimation (AIPE) approach plans the necessary sample size so that the confidence interval for the parameter of interest will have an expected width that is sufficiently narrow. We develop the AIPE approach to sample size planning for the RMSEA in an effort obtain an accurate estimate of the population RMSEA so that better conclusions can be drawn about the appropriateness of the fitted model. Analytic developments are made and a Monte Carlo simulation study verified the effectiveness of the procedures in realistic situations.
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