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Sensitivity of the chi-squared goodness-of-fit test to the partitioning of data

Gianna Boero, Jeremy Smith and Kenneth Wallis ()

No 269588, Economic Research Papers from University of Warwick - Department of Economics

Abstract: In this paper we conduct a Monte Carlo study to determine the power of Pearson’s overall goodness-of-fit test as well as the “Pearson analog” tests (see Anderson (1994)) to detect rejections due to shifts in variance, skewness and kurtosis, as we vary the number and location of the partition points. Simulations are conducted for small and moderate sample sizes. While it is generally recommended that to improve the power of the goodness-of-fit test the partition points are equiprobable, we find that power can be improved by the use of non-equiprobable partitions.

Keywords: Agricultural and Food Policy; Research Methods/ Statistical Methods (search for similar items in EconPapers)
Pages: 34
Date: 2004-01-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Related works:
Journal Article: The Sensitivity of Chi-Squared Goodness-of-Fit Tests to the Partitioning of Data (2005) Downloads
Working Paper: Sensitivity of the Chi-Squared Goodness-of-Fit Test to the Partitioning of Data (2004) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:ags:uwarer:269588

DOI: 10.22004/ag.econ.269588

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