Evaluating the statistical power of goodness-of-fit tests for health and medicine survey data

Conference item

Steele, M., Smart, N., Hurst, C. and Chaseling, J.. (2009). Evaluating the statistical power of goodness-of-fit tests for health and medicine survey data. In R.S. Anderssen, R.D. Braddock and L.T.H. Newham (Ed.). The 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. United States of America: Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, July 2009. pp. 192 - 196
AuthorsSteele, M., Smart, N., Hurst, C. and Chaseling, J.
Abstract

Goodness-of-fit test statistics are widely used in health and medicine related surveys however little regard is usually given to their statistical power. This paper investigates the simulated power of five categorical goodness-of-fit test statistics used to analyze health and medicine survey data collected on a 5-point Likert scale. The test statistics used in this power study are Pearson’s Chi-Square, the Kolmogorov-Smirnov test statistic for discrete data, the Log-Likelihood Ratio, the Freeman-Tukey and the special case of the Power Divergence statistic defined by Cressie and Read (1984). Recommendations based on these simulations are provided on which of these goodness-of-fit test statistics is the most powerful overall and which is the most powerful for the predefined uniform null against the four general shaped alternative distributions (see Figure 1) investigated in this paper.

Keywordsgoodness-of-fiit; power; chi-square tesets; discrete
Year2009
Journal18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation
PublisherModelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, July 2009
Scopus EID2-s2.0-80053039140
Web address (URL)http://www.mssanz.org.au/modsim09/A2/steele.pdf
Open accessOpen access
Publisher's version
License
Page range192 - 196
ISBN9780975840078
Research GroupSchool of Allied Health
Additional information

© Copyright The Modelling and Simulation Society of Australia and New Zealand Inc. and the International Association for Mathematics and Computers in Simulation, 2009. All rights reserved.

Place of publicationUnited States of America
EditorsR.S. Anderssen, R.D. Braddock and L.T.H. Newham
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