Variables
Independent Variable (IV): Intervention/Treatment
Dependent Variable (DV): The outcome of the intervention or what we want the intervention/treatment to change.
Experimental Control: Confidence that change in the DV is due to change in the IV.
Intervention Designs
Between Subjects: Participants are assigned to multiple groups in which they only receive one intervention. The groups are compared to determine the effects of the intervention.
Within Subjects: Two (or more) treatment are compared by observing or measuring the same group of participants in multiple treatments (participant 1 gets A-B, participant 2 gets B-A, etc.).
Types of Intervention Effects
Main Effect: Tests the effectiveness of the intervention. In other words, is there a significant difference in the dependent variables between the two intervention groups.
Moderator: A variable that tests the differential effect of the intervention based on a third variable, such as diagnostic group, timepoint, etc. (Think: For whom)
Mediator: A variable that explains the relationship between the independent variable and the dependent variable. (Think: Why?)
Effect Sizes
Effect Size: Effect sizes determine the magnitude of the effect, or the magnitude of the difference between the two groups, regardless of statistical significance.
Cohen’s d: An effect size for a numerical DV; the standardized mean difference between two groups.
Relative Risk: An effect size for categorical data. The relative risk (sometimes called relative rate) that one group has a particular outcome compared to the other. This is calculated by taking the percent of participants with the outcome of interest in the group of interest and dividing it by the percent of participants with the outcome of interest in the other group. (Think: Likelihood)
