Three broad types of evaluation designs, randomized experiments, quasi-experiments and non-experiments, address what would have happened in the absence of the health program (the “counterfactual”) in different ways.Tags: Princeton EssayKim Atherley ThesisSmall Group Problem Solving ExercisesSandwich Book Report Bulletin BoardNotes From The Underground EssaysIntroduction About Term PaperMaster Thesis At
In the appeal, Motorola claims that the Seventh Circuit is on the wrong side of a circuit split over the Foreign Trade Antitrust Improvements Act, but—perhaps more interestingly—has asked the Supreme Court to overturn the Seventh Circuit’s allowance of non-random case assignments.
Recently, the Seventh Circuit has garnered headlines for its practice of allowing a motions panel to retain a case for a decision on the merits, sometimes even without briefing and argument.
Randomized experiments, also called experimental design, are the most rigorous evaluation design, often referred to as the “gold standard.” Pre-Test/Post-Test with Random Assignment to Intervention or Comparison Groups.
In randomized experiments, study subjects (or groups) are randomly assigned to a group that receives the health program intervention (study or treatment group) or a comparison group that does not receive the intervention (control or non-treatment group).
When randomization of subjects or groups is neither practical nor feasible, a quasi-experimental design can approximate the randomized experiment.
Quasi-experimental designs use an intervention and comparison group, but assignment to the groups is nonrandom.
Thus, the program team needs to develop a robust framework during the program planning phase.
Last week, Motorola Mobility LLC petitioned the Supreme Court to review a recent adverse antitrust decision by the Seventh Circuit.
In other words, the comparison group serves as the “counterfactual” of what would have happened in the absence of the program—a key requirement in determining whether a program caused a particular health outcome.
Although considered the “gold standard,” randomized experiments often are not feasible in real-world scenarios.