Module 10: Confounding and MH Method
With categorical data, we are classifying data instead of measuring it. As a review:
Notice we never use a z test, a t test is almost always more appropriate even for large samples. Likewise, for dichotomous outcomes could use a z-test but a chi-square test is usually used in practice. Chi-square reflects categorical outcomes.
chi-square = sum((obs-exp)2 / exp), df=n-1; where n is the number of random variables or categories.
Mantel-Hansel Method
TheCochran-Mantel-Haenszel MH Methodmethod is a waytechnique tothat stratifygenerates byan confoundingestimate variablesof an association between an exposure and poolan outcome after adjusting for or taking into account confounding. We stratify the data forinto two or more levels of the confounding factor (as we did in the example above). In essence, we create a combinedseries decision,of providedtwo-by-two thattables showing the confounderassociation isbetween notthe anrisk effectfactor modifier.and outcome at two or more levels of the confounding factor, and we then compute a weighted average of the risk ratios or odds ratios across the strata.
Given the above table, we have the below MH Equations:
Though, in practice we just have the computer solve for MH estimates.