The Cochran-Armitage trend test is a statistical test used to analyze categorical data that are ordered in some way. Specifically, it is used to test for trends in proportions across ordered groups. The test is named after its developers, William Cochran and Peter Armitage.
The Cochran-Armitage trend test is a parametric test, meaning that it assumes that the data are normally distributed. It is also an asymptotic test, meaning that it is most accurate when the sample size is large. The test is commonly used in medical research, genetic studies, and other fields to assess whether there is a linear trend in a particular variable across groups.
To perform the Cochran-Armitage trend test, one must first rank the groups in order. Then, the proportion of individuals in each group who have a particular outcome (e.g. a disease or treatment success) is calculated. The test statistic, which is based on the difference between expected and observed values, is then calculated and compared to a significance level to determine if the trend is statistically significant.
Overall, the Cochran-Armitage trend test is a useful tool for analyzing trends across ordered categorical data. However, it should be used with caution and other statistical tests may also be necessary to fully understand the data.
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