2007•ResearchOnline - JCU (James Cook University)Open access

Comparing the simulated power of discrete goodness-of-fit tests for small sample sizes

Michael Craig Steele, Janet Chaseling, Cameron Paul Hurst

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Abstract

Although a variety of goodness-of-fit test statistics are used by applied researchers, studies of their power have been limited. This paper investigates the simulated power of six goodness-of-fit test statistics for discrete data for small sample sizes. The null distribution is uniform and the simulated power of each of the test statistics is calculated for a number of alternative distributions including trend, triangular, flat/platykurtic type, sharp/leptokurtic type and bimodal. KEY WORDS: Goodness-of-fit, simulation.

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Although a variety of goodness-of-fit test statistics are used by applied researchers, studies of their power have been limited. This paper investigates the simulated power of six goodness-of-fit test statistics for discrete data for small sample sizes. The null distribution is uniform and the simulated power of each of the test statistics is calculated for a number of alternative distributions including trend, triangular, flat/platykurtic type, sharp/leptokurtic type and bimodal. KEY WORDS: Goodness-of-fit, simulation.

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Available abstract

Although a variety of goodness-of-fit test statistics are used by applied researchers, studies of their power have been limited. This paper investigates the simulated power of six goodness-of-fit test statistics for discrete data for small sample sizes. The null distribution is uniform and the simulated power of each of the test statistics is calculated for a number of alternative distributions including trend, triangular, flat/platykurtic type, sharp/leptokurtic type and bimodal. KEY WORDS: Goodness-of-fit, simulation.

Key concepts: Goodness of fit, Statistics, Sample size determination, Mathematics, Kurtosis, Statistical power, Null hypothesis, Econometrics

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