<prompt> Please answer with one of the option in the bracket. Write reasoning in between . Write answer in between .Q:An investigator has conducted a prospective study to evaluate the relationship between asthma and the risk of myocardial infarction MI. She stratifies her analyses by biological sex and observed that among female patients, asthma was a significant predictor of MI risk hazard ratio 1.32, p 0.001. However, among male patients, no relationship was found between asthma and MI risk p 0.23. Which of the following best explains the difference observed between male and female patients?? A: Confounding, B: Measurement bias, C: Stratified sampling, D: Random error, E: Effect modificationn,  <response>: This question is asking about a study that found an association between asthma and myocardial infarction risk in women but not in men. It wants to know which concept best explains the difference in results between the sexes.The key thing to notice is that they stratified the analysis by sex. This means they looked at the asthma-MI relationship separately in men and women. The fact that the relationship was significant in women but not men implies that sex is modifying the effect of asthma on MI risk. So this is a case of effect modification, where the effect of one variable asthma on an outcome MI differs across levels of another variable sex. The other answer choices do not fit as well: confounding and measurement bias would not likely differ by sex, stratified sampling refers to the study design rather than analysis, and random error means chance findings rather than a systematic difference.E: Effect modification 