Displaying 2 results from an estimated 2 matches for "ubar".
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2013 Feb 14
2
Plotting survival curves after multiple imputation
...mes = list(1:m,names))
u <- array(NA, dim = c(m, k, k),
dimnames = list(1:m, names, names))
for (i in 1:m) {
fit <- analyses[[i]]
qhat[i, ] <- coef(fit)
u[i, , ] <- vcov(fit)
}
qbar <- apply(qhat, 2, mean)
ubar <- apply(u, c(2, 3), mean)
e <- qhat - matrix(qbar, nrow = m, ncol = k, byrow = TRUE)
b <- (t(e) %*% e)/(m - 1)
t <- ubar + (1 + 1/m) * b
r <- (1 + 1/m) * diag(b/ubar)
f <- (1 + 1/m) * diag(b/t)
df <- (m - 1) * (1 + 1/r)^2
if (method == "...
2007 May 17
1
MICE for Cox model
R-helpers:
I have a dataset that has 168 subjects and 12 variables. Some of the
variables have missing data and I want to use the multiple imputation
capabilities of the "mice" package to address the missing data. Given
that mice only supports linear models and generalized linear models (via
the lm.mids and glm.mids functions) and that I need to fit Cox models, I
followed the previous