Stratification and Mantel-Haenszel estimation for handling confounding and identifying effect modifiers in epidemiological studies.

1. Stratification and Mantel-
Haenszel estimation
Dr. Vignesh L, M.D. (AIIMS, New Delhi)
Senior Resident
Department of PSM
JIPMER, Puducherry

2. Confounding
Exposure Outcome
Confounding variable
?

3. How to handle confounding?
• Restriction
• Matching
• Randomization
• Stratification
• Multivariable regression

4. What if age of the participant is a ’suspect confounder’?

5. Examining the role of confounder

6. Stratification

7. Multiple stratifying groups
Cancer, Smoking, Urbanization

8. Can you notice
any other
pattern?

9. What is this phenomena?

10. 1

11. 2

12. 3

13. 4

14. 1. Calculate Crude OR and RR (without stratification)
2. Group 1 – Stratified OR for age < 50 and age > 50
3. Group 2 – Stratified RR for age < 50 and age > 50

15. Mantel-Haenszel estimation
[(10*500)/600] + [(36* 200)/400]
[(35*100)/600] + [(25* 200)/400]

16. 1000 100
900
100
1000
50
50
100
5 50
100 500

17. Factors affecting MH weight
• Total sample size
• Balance of exposed and unexposed
• Baseline disease status (among unexposed group)

18. Calculate adjusted RR and OR

20. 1

21. 2

22. 3

23. 4

24. Results
• 1 – Only confounder
• 2 – Neither confounder nor effect modifier
• 3 – Both confounder and effect modifier
• 4 – Only effect modifier

25. Limitation of MH estimation
Multi-variable regression is the savior !

26. References
• Gordis Epidemiology
• Week 9 : CONFOUNDING: MANTEL HAENSZEL
Lecture -
https://www.youtube.com/watch?v=LPr5tdAhhPA
&ab_channel=DataLearner