Author(s)

Jixiang Jixiang, Lei Zhang, William D Johnson

CSIRO Departments of Plant Science and Mathematics & Statistics, South Dakota State University, Brookings, SD 57007.
Office of Health Data and Research, Mississippi State Department of Health,570 East Woodrow Wilson, Jackson, MS 39215-1700.
Pennington Biomedical Research Center, Louisiana State University System, 6400 Perkins Road,Baton Rouge, LA 70808.

Empirical estimates of power and Type I error can be misleading if a statistical test does not perform at the stated rejection level under the null hypothesis. We employed the permutation test to control the empirical type I errors for zero-inflated exponential distributions. The simulation results indicated that the permutation test can be used effectively to control the type I errors near the nominal level even the sample sizes are small based on four statistical tests. Our results attest to the permutation test being a valuable adjunct to the current statistical methods for comparing distributions with underlying zero-inflated data structures.

Central Limit Theorem; Likelihood Ratio Test; Modified Central Limit Theorem; Permutation Test; Wald Test; Zero-Inflated Distribution

J. Jixiang, L. Zhang and W. Johnson, "The Permutation Test as an Ancillary Procedure for Comparing Zero-Inflated Continuous Distributions," Open Journal of Statistics, Vol. 2 No. 3, 2012, pp. 274-280. doi: 10.4236/ojs.2012.23033.