It helps in reducing bias. It specifically helps to eliminate treatment bias, which is where certain

treatments are preferentially given to certain participants. A clinician may feel inclined to assign a

drug with fewer side effects to healthier participants, but if participants are randomized, then this

bias goes away. Another important bias reduced by randomization is confounding, where the

treatment groups differ with respect to some characteristic that influences the outcome.

Randomization makes it easier to interpret the results of statistical testing.

It facilitates blinding. Blinding (also called masking) refers to concealing the identity of the

intervention from both participants and researchers. There are two types of blinding:

Single-blinding: Where participants don’t know what intervention they’re receiving, but the

researchers do.

Double-blinding: Where neither the participants nor the researchers know which

participants are receiving which interventions.

Note: In all cases of blinding, for safety reasons, it is possible to unblind individual

participants, as at least one of the members of the research team has the authority to unblind.

Blinding eliminates bias resulting from the placebo effect, which is where participants tend to

respond favorably to any treatment (even a placebo), especially when the efficacy variables are

subjective, such as pain level. Double-blinding also eliminates deliberate and subconscious bias

in the investigator’s evaluation of a participant’s condition.

The simplest kind of randomization involves assigning each newly enrolled participant to a treatment

group by the flip of a coin or a similar method. But simple randomization may produce an unbalanced

pattern, like the one shown in Figure 5-1 for a small study of 12 participants and two treatments: Drug

(D) and Placebo (P).

© John Wiley & Sons, Inc.

FIGURE 5-1: Simple randomization.

If you were hoping to have six participants in each group, you won’t be pleased if you end up with

three participants receiving the drug and nine receiving the placebo, because it’s unbalanced. But

unbalanced patterns like this arise quite often from 12 coin flips. (Try it if you don’t believe us.) A

better approach is to require six participants in each group but shuffle those six Ds and six Ps around

randomly, as shown in Figure 5-2.

© John Wiley & Sons, Inc.

FIGURE 5-2: Random shuffling.