Timeline for Should one control for non-confounders?
Current License: CC BY-SA 4.0
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| Nov 20, 2018 at 16:47 | comment | added | AdamO | @TomPape you are right on the nose. We never know the actual role of variables in analysis, and subtle differences in timing, interpretation, or recall bear out significantly on analyses. It's a rich area of discussion that's lacking in most applied analyses. I wholeheartedly encourage any analyst to devote discussion toward the apriori model selection/justification. | |
| Nov 20, 2018 at 16:00 | vote | accept | Tom Pape | ||
| Nov 20, 2018 at 15:58 | comment | added | Tom Pape | Thank you Adam for your super quick response. I have never heard the term precision variable before, but googling let me to some additional explanations (e.g. ics.uci.edu/~dgillen/STAT211/Handouts/… slide 20-33). Obviously, in practice one normally controls for variables “just in case” they might be confounders. Furthermore, the impact of such precision variables is often negligible in real-life data with respect to driving down the residuals substantially. Thus, precision variables will always be an afterthought - but good to know that they exist. | |
| Nov 20, 2018 at 14:23 | history | answered | AdamO | CC BY-SA 4.0 |