Research And Evaluation Practice Test

When you can’t randomize who gets the program, you can still estimate its impact by looking at how outcomes change over time in the area with the program compared to a similar area without it. This approach uses the difference of changes: you measure how the outcome moves from before to after in the program area and subtract how it moved in the nonprogram area. The idea is that anything that affects both areas similarly over time (like broader economic shifts) gets canceled out, leaving the net effect attributable to the program. This works best if the two areas would have followed parallel trends if the program hadn’t been implemented. A randomized trial would assign the program at random, which is often not feasible and doesn’t inherently require comparing changes over time with a nonprogram area. A cross-sectional design only looks at one point in time, missing the before-versus-after comparison. A case series describes outcomes in a group without a comparator, so it can’t isolate the program’s effect.