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R1.2: appropriate statistical model for multiple observations per study? #2
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A related concern is that the tests for statistically significant differences in the univariable analysis appear problematic. When you use the Kruskal-Wallis test you are assuming independence of observations. But here the observations are not statistically independent of one another - in many cases multiple observations are being taken from the same study (and there is likely to be a high degree of within-study correlation). By not taking into account the within-study correlation I think you exaggerate the significance of the differences between model types. That might explain some of the odd results in Table C1 (for example a statistically significant positive relationship between HCT behaviour change and the incidence reduction, but a significant negative relationship between HCT behaviour change and the cumulative % of infections averted). If you use a meta-regression approach, you should be able to control for the within-study correlation.
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