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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 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).
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.
By contrast, other forms of blinding, used after the assignment of treatments, serve primarily to reduce ascertainment bias. Second, from a practical standpoint, concealing treatment assignment up to the point of allocation is always possible, regardless of the study topic, whereas blinding after allocation is not attainable in many instances ...
An operational confounding can occur in both experimental and non-experimental research designs. This type of confounding occurs when a measure designed to assess a particular construct inadvertently measures something else as well. [20] A procedural confounding can occur in a laboratory experiment or a quasi-experiment. This type of confound ...
Social science research is particularly prone to observer bias, so it is important in these fields to properly blind the researchers. In some cases, while blind experiments would be useful, they are impractical or unethical. Blinded data analysis can reduce bias, but is rarely used in social science research. [39]
Statistical bias exists in numerous stages of the data collection and analysis process, including: the source of the data, the methods used to collect the data, the estimator chosen, and the methods used to analyze the data. Data analysts can take various measures at each stage of the process to reduce the impact of statistical bias in their ...
Adaptive bias is the idea that the human brain has evolved to reason adaptively, rather than truthfully or even rationally, [clarification needed] and that cognitive bias may have evolved as a mechanism to reduce the overall cost of cognitive errors as opposed to merely reducing the number of cognitive errors, when faced with making a decision under conditions of uncertainty.