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There are different ways that blocking can be implemented, resulting in different confounding effects. However, the different methods share the same purpose: to control variability introduced by specific factors that could influence the outcome of an experiment.
The regression uses as independent variables not only the one or ones whose effects on the dependent variable are being studied, but also any potential confounding variables, thus avoiding omitted variable bias. "Confounding variables" in this context means other factors that not only influence the dependent variable (the outcome) but also ...
The stronger the confounding of treatment and covariates, and hence the stronger the bias in the analysis of the naive treatment effect, the better the covariates predict whether a unit is treated or not. By having units with similar propensity scores in both treatment and control, such confounding is reduced.
This finding, if generalizable to other tasks and disciplines, would discount the potential of expert-level training as a cognitive bias mitigation approach, and could contribute a narrow but important idea to a theory and practice of cognitive bias mitigation. Laboratory experiments in which cognitive bias mitigation is an explicit goal are rare.
Minimize allocation bias (or confounding). This may occur when covariates that affect the outcome are not equally distributed between treatment groups, and the treatment effect is confounded with the effect of the covariates (i.e., an "accidental bias" [ 50 ] [ 56 ] ).
The goal of matching is to reduce bias for the estimated treatment effect in an observational-data study, by finding, for every treated unit, one (or more) non-treated unit(s) with similar observable characteristics against which the covariates are balanced out (similar to the K-nearest neighbors algorithm).
No app can fix your focus. Here’s how CNN’s Upasna Gautam ditched the productivity hacks and embraced the basics to get the most out of life.
Bias can also be mitigated in a cohort study when selecting participants for the cohort. RCTs may not be suitable in all cases; such as when the outcome is a negative health effect and the exposure is hypothesized to be a risk factor for the outcome. Ethical standards, and morality, would prevent the use of risk factors in RCTs.