has_specified_input has_specified_output achieves_planned_objective study design independent variable study design dependent variable data transformation test of association between categorical variables false positive rate polychotomous variable dichotomous variable association between categorical variables testing objective Cochran-Armitage test for trend 1 1 1 http://en.wikipedia.org/wiki/Cochran%E2%80%93Armitage_test_for_trend Orlaith Burke Alejandra Gonzalez-Beltran CATT Philippe Rocca-Serra The Cochran-Armitage test is a statistical test used in categorical data analysis when the aim is to assess for the presence of an association between a dichotomous variable (variable with two categories) and a polychotomous variable (a variable with k categories). The two-level variable represents the response, and the other represents an explanatory variable with ordered levels. The null hypothesis is the hypothesis of no trend, which means that the binomial proportion is the same for all levels of the explanatory variable For example, doses of a treatment can be ordered as 'low', 'medium', and 'high', and we may suspect that the treatment benefit cannot become smaller as the dose increases. The trend test is often used as a genotype-based test for case-control genetic association studies. 2 by n contingency table p-value Cochran-Armitage Chi-Square Statistic for Trend ready for release