Explaining community-level variance in group randomized trials

Between-community variance or community-by-time variance is one of the key factors driving the cost of conducting group randomized trials, which are o ften very expensive. We investigated empirically whether between-community variance could be reduced by controlling individual- and/or community-level covariates and identified these covariates from four large community-based group randomized trials or surveys: the Working Well Trial; Kaiser Adolesc ent Survey; Kaiser Adults Survey; and the Eating Patterns Study. We found t hat adjusting for covariates will often substantially reduce the between-co mmunity variance component. Therefore investigators could block the communi ties according to these covariates, or adjust for these covariates to impro ve the power of community trials. We found that the community-by-time varia nce components are always near zero in these data sets, especially for the surveys where a cohort was followed over time. The covariate adjustment had less impact on reducing the community-by-time variance for the cohort samp les than for the cross-sectional samples. This suggests that blocking may n ot be necessary for the design of the group randomized trials where the cha nge from baseline is of primary interest. The Working Well Trial data were used to illustrate this point. Copyright (C) 1999 John Wiley & Sons, Ltd.