Critical thinkingArticle: Pearl (2018)Confounding and deconfounding: or, slaying the lurking variable Confounding bias occurs when a variable influences both who is selected for the treatment and he outcome of the experiment.Sometimes the confounders are known. Other times they are merely suspected and act as a ‘lurking third variable’.If we have measurements of the third variable, then it is very easy to deconfound the true and spurious effects.Statisticians both over- and underrate the importance of adjusting for possible confoundersOverrate in the sense that they often control for many more variables than they need to and even for variables that they should not control forUnderrate in the sense that they are loath to talk about causality at all, even if the controlling has been done correctly. Knowing the set of assumptions that stand behind a given conclusion is not less valuable than attempting to circumvent those assumptions with and RCT, which has complications on its own. The one circumstance under which scientists will abandon some of their reticence to talk about causality is when they have conducted a randomized controlled trial (RCT).Randomization brings two benefits:It eliminates confounder biasIt enables the researcher to quantify...