Cluster Unit Randomized Trials

4. Common Designs

Commonly Adopted Cluster Randomization Designs

The reduced effective sample size associated with cluster randomization increases the risk of chance imbalance between intervention groups on prognostically important baseline characteristics. This in turn has strongly influenced investigators to use some form of restricted randomization in the formal allocation scheme. As a result the matched-pair design, although seen only infrequently in individually randomized trials, has become very popular for CRTs, particularly when the total number of available clusters is small. This design requires members of a pair (stratum) to be first matched on known risk factors for outcome, with each member then randomized to either the intervention or control group.

In the COMMIT trial (Example E above) the participating communities were matched on several baseline characteristics, including community size, population density, demographic profile, community structure, and geographical proximity. The attraction of such extensive matching is the assurance it provided that the groups compared were well balanced on baseline factors potentially related to smoking cessation. This assurance would seem to be particularly important in a trial involving only 11 matched pairs, since any statistical adjustment for chance imbalance at the data analysis stage would necessarily be limited in scope. The PROBIT trial (Example C) also used this design, matching maternity hospitals with respect to geographic region, number of deliveries per year, and breastfeeding initiation rates at hospital discharge.

Example A
450 villages in Indonesia were randomly assigned to either participate in a Vitamin A supplementation scheme or serve as a control. One-year childhood mortality rates were compared in the two groups (Sommer et al., 1986).
Example B
90 families were randomly assigned to receive either treated nasal tissues or standard tissues. 24-week incidence of respiratory illness was compared in the two groups (Farr et al., 1988).
Example C
One member of each pair of 11 matched maternity hospitals in Belarus was randomly assigned to receive a breastfeeding promotion strategy, with the other member of the pair receiving a control condition based on usual practice (PROBIT trial). The rate of breastfeeding at 12 months was compared between the two groups (Kramer et al., 2001).
Example D
207 general practices were randomized to receive either a structured group education program or standard care offered to patients with newly diagnosed type 2 diabetes. A variety of response variables, including biomedical, lifestyle, and psychosocial measurements were collected over a one-year follow-up period (Davies et al., 2008).
Example E
One member of each pair of 11 matched communities was randomly assigned to a city-wide intervention that promoted the hazards of smoking with the other member serving as a control. Five-year smoking cessation rates were compared in the two groups (COMMIT Research Group, 1995).
Diwan V.K., Wahlström R., Tomson G., Beermann B., Sterky G., Eriksson B. (1995). Effects of ‘Group Detailing’ on the prescribing of lipid-lowering drugs: A randomized controlled trial in Swedish primary care. Journal of Clinical Epidemiology, 48: 705-711.
Alexander F., Roberts M.M., Lutz W., Hepburn W. (1989). Randomization by cluster and the problem of social class bias. Journal of Epidemiology and Community Health, 43:29-36.