Essay about Regression Discontinuity Design For Causal Inference

1016 Words Jan 27th, 2015 null Page
Regression-Discontinuity Design. A powerful, alternative design for causal inference that is underutilized in the health and intervention sciences is the regression discontinuity (RD) design (Thistlewaite & Campbell, 1960). In its simplest form, the RD design involves the use of a screening measure of some form that is continuous and given to all persons. A cut point or criterion is set, which determines whether individuals are assigned to an intervention condition or a comparison condition. The cut point is determined on the basis of need or a cost-benefit analysis. If an analysis of an outcome measure shows a change in the mean-level or slope-angle that occurs for individuals at the cut point, then a causal conclusion of the effectiveness (or not) of a treatment or intervention is warranted (see Greenwood & Little, 2007).
Figure 2 depicts hypothetical results of the effect of a treatment designed to increase math test scores. The horizontal axis is the screening measure and the vertical axis is the dependent variable, math test scores. The counterfactual regression line is what the regression line would look like if the treatment had no effect. In a typical RD design, the form of the counterfactual regression line is assumed. It can, however, be estimated by adding a pretest comparison group, as Wing and Cook (2013) suggested (as detailed later). Usually the counterfactual regression line will be smooth across the cutoff point, as it is in Figure 2. Assuming a smooth…

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