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...d), mean) plot(Means[,1], col="red", type = "l", ylim = c(400,700)) points(Means[,2], col="blue", type = "l") # create contrasts for hypothesis of interest # school i attend j - school i attend j' # for all schools sxa <- interaction(school, attend) sxam <- as.matrix(rbind(diag(1,10), diag(1,10) * -1)) contrasts(sxa) <- sxam summary(aov(y ~ sxa), split=list(sxa=1:10), expand.split = T) The actual problem has a few more schools, other covariates, considerably more students, and is somewhat unbalanced. Thanks, Scot -- Scot W. McNary...