Shulou(Shulou.com)06/01 Report--

In this issue, the editor will bring you about the application of Cochran-Armitage trend test in association analysis. The article is rich in content and analyzes and narrates it from a professional point of view. I hope you can get something after reading this article.

Cochran-Armitage trend test, referred to as CAT trend test for short, is a test method proposed by William Cochran and Peter Armitage to analyze the correlation between two classification variables. Different from the chi-square test, this method requires that one of the classification variables must have only two categories, and the other variable is an ordered classification variable.

In short, this method is suitable for processing classified data of 2 x K, where K is an ordered variable and the minimum value of K is 3. This method is used to explore whether there is a linear relationship between the incidence of ordered variables in each group and the corresponding order, which is similar to logical regression.

The figure below shows an example of Knights 3.

CAT test constructs a statistic T. The calculation process is as follows

Here t represents the weight of each k, which is the sort order of k variables, also known as the trend of k. The difference between the two groups is reflected by N1 x R2-N2 x R1, and the different values of k are weighted by the coefficient t, that is, the original difference result is multiplied by a coefficient. The statistic T is regarded as the sum of the weighted differences between the two groups.

The chi-square test is carried out on the statistic, and the calculation formula is as follows.

This method is often used for genotypic association analysis of case/control, as shown below.

In the analysis, the genotypes can be weighted according to the genetic model. For the association analysis of case/control, the genetic model is unknown, and the additive model, also known as co-dominance model, is usually used for analysis. The number of mutant Allel included needs to be added, and the corresponding coefficient is (0, 1, 2).

Compared with the chi-square test, its inspection performance is better. The code analyzed in R for the above example is as follows.

The p value of Chi-square test is not significant, but the p value of CAT trend test is significant. CAT test is called trend chi-square test. As an effective supplement of traditional chi-square test, it is widely used in association analysis, which strengthens the efficiency of test and can better mine correlation signals.

This is the application of Cochran-Armitage trend test in association analysis shared by the editor. If you happen to have similar doubts, you might as well refer to the above analysis to understand. If you want to know more about it, you are welcome to follow the industry information channel.

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