Finally, to help interpret these multigroup SEM comparisons, we performed a post-hoc examination of the model variable means for different gender and age groups and tested differences using the Mann-Whitney test, which tests differences between two groups on ordinal scales of measurements.
In parallel, we tested differences in development of scent glands between males exhibiting different parasite load using an ANOVA.
Under this ranking of significance, we tested differences in either p-distance or Ks distance between different pairs of phenotypes by the Wilcoxon test (fig. 3 and Table S2, Supplementary Material online).
However, about ten years ago we began to be able to interrogate much of the human genome simultaneously, through genome-wide association studies (GWAS) that tested differences between our genes 500,000 at a time.
Moreover, the model tested differences in utility (or preference) between men and women or the two educational groups.
The model tested differences in utility for each of the four included mode choices – car as a driver, car as a passenger, public transport and walking.
We also tested differences of genotypes between groups by analysis of multiple inheritance models but they were not statistically significant (Table 3).
We tested differences in the sex ratio (female:male:hermaphrodite) among the sibling groups with the χ2 tests using chisq.test(x).
The study also tested differences between alcohol dependent women with or without a history of sexual abuse on variables that might affect treatment planning.
In closing, we tested differences between the ratings by Ra and Re using ORMs.
For the sake of brevity, we present only the tested differences in strains with respect to an arbitrarily designated reference strain, D2 1232.
