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library(inferference) head(vaccinesim)
example1 <- interference( formula = Y | A | B ~ X1 + X2 + (1|group) | group, allocations = seq(.2,.8, by = .1), data = vaccinesim, randomization = 2/3, method = 'simple')
deff <- direct_effect(example1) x <- deff$alpha1 y <- as.numeric(deff$estimate) u <- as.numeric(deff$conf.high) l <- as.numeric(deff$conf.low) plot(c(min(x), max(x)),c(-.15, .25), type = 'n', xlab = expression(alpha), ylab = expression(widehat(DE) * "(" * alpha * ")"), bty = 'n') polygon(c(x, rev(x)), c(u, rev(l)), col = 'skyblue', border = NA) lines(x, y, cex = 2)
ieff.4 <- ie(example1, allocation1 = .4) x <- ieff.4$alpha2 y <- as.numeric(ieff.4$estimate) u <- as.numeric(ieff.4$conf.high) l <- as.numeric(ieff.4$conf.low) plot(c(min(x), max(x)),c(-.15, .25), type = 'n', xlab = expression(alpha * "'"), ylab = expression(widehat(IE) * "(" * 0.4 * "," * alpha * "'" * ")")) polygon(c(x, rev(x)), c(u, rev(l)), col = 'skyblue', border = NA) lines(x, y, cex = 2)
ieff <- subset(example1$estimates, effect == 'indirect') x <- sort(unique(ieff$alpha1)) y <- sort(unique(ieff$alpha2)) z <- xtabs(as.numeric(estimate) ~ alpha1 + alpha2, data= ieff) contour(x, y, z, xlab = expression(alpha), ylab = expression(alpha * "'"))
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