Pattern Heterogeneity via Distributional Differences Across
Statistical hypothesis testing of pattern heterogeneity via
differences in underlying distributions across two or more contingency
tables. Three tests are included: the comparative chi-squared test
(Song et al, 2014) <10.1093> (Zhang et al, 2015)
<10.1093>, the Sharma-Song test, and the heterogeneity test.
Under the null hypothesis that row and column variables are statistically
independent and joint distributions are equal, their test statistics all
follow an asymptotically chi-squared distribution. These options test for
heterogeneous patterns that differ in either the first order (marginal) or
the second order (joint distribution deviation from product of marginals).
Second-order differences may reveal more fundamental changes than
first-order differences across heterogeneous patterns.10.1093>10.1093>