Summary Estimators: Mantel-Haenszel Method

Lead Author(s): Jeff Martin, MD

This is one method for calculating summary adjusted estimators when making adjustments in the measure of association.

Summary Estimators: Mantel-Haenszel Method

Given the Woolf's Method problem with cells of zero, the Mantel-Haenszel method is more widely used.

Data for Mantel-Haenszel's Method

0417_1A_chi.JPG

Step 1 - Weight Using the Native Odds Ratio Scale

0417_1B_sum.JPG
Here, we are working with the plain old native odds ratio scale.

0417_1C_weight.JPG

In other words, the weight is related to the variance, but a special form of the variance, that is, when there is no association.

Example: Summary Adjusted Effect Using Mantel-Haenszel Method

In the example of AZT use we need to determine the summary adjusted effect, using the Mantel-Haenszel Method. We obtain an summary estimate for the association between AZT use and HIV seroconversion after adjusting for severity of needlestick.

0417_2a_number.JPG

The summary adjusted estimate is 0.3. The crude estimate was 0.6 and not even statistically significant.

Variance Associated with No Effect

Now, you might wonder why we using a variance associated with an odds ratio of no effect if indeed there is an effect in the stratum. Note: another intuitive approach to understanding the MH formula is to note that ad/n is a pretty good approximation of the numerator ad in an odds ratio and bc/N is a pretty good approximation of the denominator of the odds ratio.

Pros and Cons of Mantel-Haenszel's Methods

The Mantel-Haenszel technique, although not as straightforward conceptually as the Woolf technique, which directly uses stratum-specific variances, has many advantages: