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A COMPARISON OF POWER APPROXIMATIONS FOR SATTERTHWAITE'S TEST
Rachael L Disantostefano1, Keith E Muller
1Family Health International, P.O. Box 13950, Research Triangle Park, North Carolina 27709.
Communications in Statistics: Simulation and Computation
|October 1, 2013
Summary
This study introduces simple approximations for Satterthwaite test power calculations, reducing computational load and increasing accessibility for statistical analysis of normal population means.
Area of Science:
- Statistics
- Statistical Inference
- Hypothesis Testing
Background:
- Many statisticians favor heterogeneity-tolerant tests for comparing means of two independent normal populations.
- Existing methods for calculating the power of the Satterthwaite test statistic involve complex numerical integration.
Purpose of the Study:
- To present simple and accurate approximations for the power of the Satterthwaite test statistic.
- To reduce the computational burden and enhance the accessibility of power calculations.
Main Methods:
- Evaluated four power approximation methods for the Satterthwaite test.
- Assessed performance across various test sizes, sample sizes, variance ratios, and noncentrality parameters.
Main Results:
- Identified a recommended approximation method based on a ratio of expected values.
- Demonstrated substantial reductions in computational requirements for power curve plotting and programming.
Conclusions:
- The proposed approximations offer a computationally efficient and simpler alternative for Satterthwaite test power calculations.
- Increased availability of power calculations can support wider statistical practice.
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