1 | xanova.lmer(fit, Llist, df = NULL, clevel = 0.95)
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fit |
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Llist |
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df |
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clevel |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | ##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (fit, Llist, df = NULL, clevel = 0.95)
{
warning("xanova.lmer uses Chi-Square tests")
ret <- list()
for (ii in 1:length(Llist)) {
L <- rbind(Llist[[ii]])
QR <- qr(L)
R <- qr.R(QR)
dfH <- QR$rank
eta <- R %*% fixef(fit)
vv <- R %*% vcov(fit) %*% t(R)
chisq <- t(eta) %*% qr.solve(vv, eta)
test <- list(ChiSquare = chisq, DF = dfH, `p-value` = 1 -
pchisq(chisq, dfH))
ret[[ii]]$anova <- test
eta <- L %*% fixef(fit)
vv <- diag(L %*% vcov(fit) %*% t(L))
etasd <- sqrt(vv)
zval <- c(eta/etasd)
aod <- cbind(Estimate = c(eta), Std.Error = etasd, `z-value` = zval,
`p-value` = 2 * pnorm(-abs(zval)))
if (!is.null(clevel)) {
hw <- qnorm(1 - (1 - clevel)/2) * etasd
aod <- cbind(aod, LL = eta - hw, UL = eta + hw)
labs <- paste(c("Lower", "Upper", format(clevel)))
colnames(aod)[ncol(aod) + c(-1, 0)] <- labs
}
aod <- as.data.frame(aod)
class(aod) <- c("estimate.lme", "data.frame")
ret[[ii]]$estimate <- aod
}
}
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