Timeline for Differences in potential explanations between observational and experimental studies
Current License: CC BY-SA 3.0
3 events
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| Mar 22, 2018 at 18:35 | comment | added | Gregg H | Sorry, I think I may have phrased my parenthetical comment about confounding in 2nd ¶ a little weirdly. I meant to suggest that confounding would be an issue with observational designs, not experimental. Regarding the second query, the hope is that randomization is accounting for this, but the nature of randomization is such that we could randomly end up with very disparate groups (which would introduce confounding back into the picture). (Then, it becomes an issue of semantics: ¿did the randomization cause the result or the confounding variable?) | |
| Mar 22, 2018 at 18:18 | comment | added | Jean Luc Picard | But isn't it inherent in an experiment that a correlation couldn't result from a variable C causing A and B, because in an experiment we completely control A? For instance, if we observe whether people who eat kale are less likely to contract cancer, it might be that people who are health-conscious are eating kale, and are also doing other things that make them less likely to contract cancer. If we had an experiment where we randomly assigned some people to eat kale and others not to, we'd know that wasn't happening. Aren't we, then, inherently controlling for part of (3) in an experiment? | |
| Mar 22, 2018 at 18:06 | history | answered | Gregg H | CC BY-SA 3.0 |