Cluster-randomized trials, in which health interventions are allocated randomly to
intact clusters or communities rather than to individual subjects, are increasingly
being used to evaluate disease control strategies both in industrialized and in developing
countries. Sample size computations for such trials need to take into account between-cluster
variation, but field epidemiologists find it difficult to obtain simple guidance on
In this paper, we provide simple formulae for sample size determination for both unmatched
and pair-matched trials. Outcomes considered include rates per person-year, proportions
and means. For simplicity, formulae are expressed in terms of the coefficient of variation
(SD/mean) of cluster rates, proportions or means. Guidance is also given on the estimation
of this value, with or without the use of prior data on between-cluster variation.
The methods are illustrated using two case studies: an unmatched trial of the impact
of impregnated bednets on child mortality in Kenya, and a pair-matched trial of improved
sexually-transmitted disease (STD) treatment services for HIV prevention in Tanzania.