What is cochran armitage test?

Cochran Armitage test, also known as trend test, is a statistical method used to test for trend in proportions across ordered groups of categorical data. It is used when you have a binary dependent variable (success or failure) and an independent variable that is ordinal in nature (such as increasing dosage levels of a drug, or increasing levels of a disease severity).

The test is based on comparing the observed frequencies of the success outcomes with the expected frequencies, assuming that there is a linear trend across the groups. The test calculates a Z-score that measures the deviation of the observed trend from the expected trend, under the null hypothesis that there is no trend.

The p-value from the Cochran-Armitage test will tell you whether there is a statistically significant trend in the proportions across the groups. If the p-value is less than your chosen level of significance (usually 0.05), you can reject the null hypothesis of no trend, and conclude that there is evidence for a trend in the proportions across the groups.

The Cochran-Armitage test is commonly used in medical and epidemiological studies to investigate the relationship between ordinal predictor variables and binary outcomes. It is implemented in most statistical software packages, including R, SAS, and Stata.