Methods Of Random Assignment

Widely accepted as the “gold standard” of evaluation designs, a randomized controlled trial, if properly implemented, yields the most robust and credible estimates of a program’s effects.Typically, in this design, individuals who are eligible for a program are randomly assigned one by one to a treatment group whose members receive the specified intervention or to a control group whose members are embargoed from the program but free to receive other available services.

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So even if only some teachers received the professional development, other teachers would also learn about it, albeit at second hand.

The diffusion of the key concepts and practices associated with the treatment among those not formally slated to receive that treatment — known as “contamination” in research parlance — would make a clean test of program impacts impossible.

Like random assignment of individuals, random assignment of groups yields unbiased conclusions about program impacts, and there are a number of circumstances in which random assignment of groups may be the preferred option.

First, the program services being tested may be directed toward everyone in the group.

Finally, in some situations, school officials or other administrators might not agree to random assignment of individuals but might permit an entire organization, such as a school, to be part of a study that randomized organizations.

In these cases, cluster random assignment may be the only option.The presence of two sources of sampling error means that the impact estimates produced by a cluster randomized trial, although unbiased, will inevitably be less precise than the impact estimates produced by a randomized trial involving the same number of ungrouped individuals.This is a key factor that researchers consider when they design cluster randomized trials, particularly when they determine the number of groups (e.g., schools, agencies) and the number of individuals in each group needed to produce impacts that are both statistically significant and large enough to be policy-relevant.If a different mix of individuals had been randomly assigned to a study’s treatment and control groups, a somewhat different impact estimate would have been obtained.This reality, which can be referred to as “randomization error,” creates uncertainty about whether the estimated impact is the true impact of the intervention.The groups in question may be organizations, like schools or hospitals or businesses, or they may be geographically defined, like neighborhoods or even cities.These groups typically exert an influence of some kind on their individual members.Thus, a whole-school reform effort, for example, may seek to change the everyday practices of all administrators, teachers, staff, and students in a school; an effort to boost employment in a public housing development may be aimed at all of the development’s residents, not just selected residents.Second, even if the services are not directed toward everyone, they may have “spillover” effects that would make a fair test of the services impossible.The methods examined combine different types of comparison groups, with different propensity score balancing approaches and different statistical models.has been known for its use of randomized controlled trials to measure the effects of social and educational policy initiatives.


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