data(nhanes)

nhanes$hyp <- as.factor(nhanes$hyp)

imp <- mice(nhanes,method=c("polyreg","pmm","logreg","pmm"), seed = 23109)

m <- imp$m

Q <- rep(NA, m)

U <- rep(NA, m)

for (i in 1:m) {
  Q[i] <- mean(complete(imp, i)$hyp)
  U[i] <- var(complete(imp, i)$hyp) / nrow(nhanes) # (standard error of   estimate)^2
}

pool.scalar(Q, U, method = "rubin") # Rubin 1987

> pool.scalar(Q, U, method = "rubin") # Rubin 1987
$m
[1] 5

$qhat
[1] NA NA NA NA NA

$u
[1] 0.006666667 0.009066667 0.008400000 0.009066667 0.006666667

$qbar
[1] NA

$ubar
[1] 0.007973333

$b
[1] NA

$t
[1] NA

$r
[1] NA

$df
[1] NA

$fmi
[1] NA

$lambda
[1] NA