miMeanSEList(object, estimate = "estimate", se = "se",
df = "df", n = "n", sse = F, cov)
mi object whose imputations are lists.
object which contain estimates, standard
errors, degrees of freedom, sample size, and covariance matrices,
respectively, or may be objects containing those values.
TRUE, then the numerical values for
se are assumed to contain
squared standard errors.
This function extracts data from
object, then
calls
miMeanSEDefault to perform calculations.
estimate, and at least one of
se and
cov
, are required.
If
df and
n are not supplied (or the corresponding
elements of
object do not exist) then some components of the
output will contain missing values.
fit <- miEval(lm(chol14~., data = cholesterolImpExample))
sumfit <- miEval(summary(fit))
coefs <- miEval(coef(sumfit))
coefs[[1]] # note estimates and std errors
miMeanSEList(miEval(list(estimate = coefs[,1],
se = coefs[,2])))