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The Sensitivity of Chi-Squared Goodness-of-Fit Tests to the Partitioning of Data

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Author Info

  • Gianna Boero
  • Jeremy Smith
  • Kenneth Wallis

Abstract

The power of Pearson's overall goodness-of-fit test and the components-of-chi-squared or “Pearson analog” tests of Anderson [Anderson, G. (1994). Simple tests of distributional form. J. Econometrics 62:265-276] to detect rejections due to shifts in location, scale, skewness and kurtosis is studied, as the number and position of the partition points is varied. Simulations are conducted for small and moderate sample sizes. It is found that smaller numbers of classes than are used in practice may be appropriate, and that the choice of non-equiprobable classes can result in substantial gains in power.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

Volume (Year): 23 (2005)
Issue (Month): 4 ()
Pages: 341-370

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Handle: RePEc:taf:emetrv:v:23:y:2005:i:4:p:341-370

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Related research

Keywords: Pearson's goodness-of-fit test; Component tests; Monte Carlo; Number of classes; Partitions;

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Cited by:
  1. Hasebe, Takuya & Vijverberg, Wim P., 2012. "A Flexible Sample Selection Model: A GTL-Copula Approach," IZA Discussion Papers 7003, Institute for the Study of Labor (IZA).

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