Exact nonparametric methods have an advantage over
asymptotic methods since they remain valid for very small
sample sizes, as well as for data that are sparse, skewed, or
heavily tied.
Below are highlights of the capabilities of the SAS/STAT procedures that can be used to perform exact conditional inference:
- exact p-values and confidence intervals for many test statistics and measures based on
one-way and n-way frequency and contingency tables
- exact tests for the parameters of a logistic regression model
- exact tests for the parameters of a Poisson regression model
- exact versions of the Cochran-Armitage and Peto tests that use permutation distributions
- exact p-values for nonparametric tests
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here for a more detailed summary.