Say you have a trial with 100 participants. Everything is ready to go and you can’t wait to see the results! There’s just one problem: how do you decide which participants belong in the intervention group and who goes to the control group?
Research can get a little particular with procedures, and randomization is one of them. But don’t worry, because BetaGov has your back.
You see, bias is a sneaky thing, and it’s imperative that bias—even if unintentional—has no influence on which participants are exposed to the intervention and who gets assigned to the control group. Otherwise, your trial results may not reflect only the effect of the intervention.
So we pay close attention to random assignment. We want to do everything possible to ensure you get scientifically valid results.
The specific protocol for how to randomize depends on your trial. For example, an education trial involving 20 schools might randomize at the school level. Ten schools are in the intervention group, and ten are in the control group.
One way to randomize the participants (schools) is to pick names out of a hat. Yes, it really is that simple!
Sometimes your participants won’t all start the trial at the same time. This may happen if your trial is testing a service for new students or clients who may trickle into your school or agency. What do you do if your participants aren’t pre-selected? In this case, you would want to assign every other new student or client to the intervention group, and every other to the control group. It should be noted, however, that this type of randomization schedule can present its own set of potential complications, which is why we’ll work with you on the trial’s design.
There are also techniques like block (or urn) randomization that help ensure balance of certain characteristics throughout the randomization process; these are especially useful in studies with small samples. The good news is that RCTs are our specialty, so you never have to worry about getting this critical procedure right. The BetaGov team can assist with randomizing—or manage it altogether—so that you can get on with running your trial and getting results.
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