Tobacco intervention studies that employ a community trial design require adjustment to the usual analytic methods to account for the allocation of intact social groups to study conditions and the positive intraclass correlation (p) that is inevitable in such a design. In the absence of valid estimates of the relevant p, investigators seeking to establish an appropriate sample size could only guess about the magnitude of the problem. We recently published estimates of p for common measures of adolescent tobacco use, but those estimates were unadjusted for potential covariates and so represented an upper limit on the magnitude of p. This report demonstrates how estimates of intraclass correlation may be substantially reduced through regression adjustment for easily measured covariates. Results show that both the p and the residual variance can be reduced, by an average of 20 and 11%, respectively, offering greater efficiency for investigators who plan future studies and who are able to measure those covariates in their studies. Future work should seek both to replicate this work and to extend it; for example, to cohort designs where the improvements might be even greater.