What are the difficulties and problems with population-based research on a possible hormonal contraceptive/HIV link? Are they important enough to undermine the conclusions of this type of research?
When researchers examine population-based studies, one of the main things they are alert to is the possibility of “confounding.” In brief, this means the possibility that an effect which appears to be the result of a factor that the study is measuring is, in fact, the result of another, different factor that the study is not measuring – or at least not measuring accurately enough. To take a fictional example: If we assume that cigarette smokers tend to get less exercise than non-smokers, then a study which looked only at the relationship between exercise and lung cancer (without measuring cigarette smoking!) might conclude that less exercise leads to greater risk of lung cancer. In fact, of course, it is unlikely that this is true. What is more likely is that cigarette smoking (which was not measured in the study) is the real cause of increased lung cancer risk, and that lower exercise (which was measured in the study) is merely a behavior associated with cigarette smoking but not itse
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