Mauchly’s test for sphericity can be run in the majority of statistical software, where it tends to be the default test for sphericity. Mauchly’s test is ideal for mid-size samples. It may fail to detect sphericity in small samples and it may over-detect in large samples.

If the test returns a small p-value (p ≤.05), this is an indication that your data has violated the assumption. The following picture of SPSS output for ANOVA shows that the significance “sig” attached to Mauchly’s is .274. This means that the assumption has not been violated for this set of data.

Kempthorne uses the randomization-distribution and the assumption of * unit treatment additivity* to produce a * derived linear model* , very similar to the textbook model discussed previously. [29] The test statistics of this derived linear model are closely approximated by the test statistics of an appropriate normal linear model, according to approximation theorems and simulation studies. [30] However, there are differences. For example, the randomization-based analysis results in a small but (strictly) negative correlation between the observations. [31] [32] In the randomization-based analysis, there is * no assumption* of a * normal* distribution and certainly * no assumption* of * independence* . On the contrary, * the observations are dependent* !

Note that the desired p-adjustment method will vary by researcher, study, etc. Here, we will assume an alpha level of .05 for all tests, effectively making no adjustment for the family-wise Type I error rate.

These results indicate that there are are no statistically significant pairwise differences between the treatment groups and that all of the comparisons between age groups are statistically significant. The age group means are 8 for young, 5 for mid, and 2 for old. Consequently, we are inclined to conclude that, regardless of treatment, young patients are going to be most responsive, followed by middle aged patients, followed by older ones. However, there is insufficient support to differentiate between the effectiveness of the treatment methods themselves.