Packages a gmm_imputation as a mice::mids object so that an arbitrary
model estimand can be fitted and pooled with the established mice workflow.
The joint Gaussian-mixture imputations – including the multimodal and
heteroscedastic shapes a univariate imputer cannot produce – flow through
unchanged; mice supplies with(), mice::pool(), and the pooled
diagnostics.
Value
A mice::mids object with m imputations.
See also
gmm_impute(), proxy_pool() for the closed-form column-mean
pooling.
Other imputation:
gmm_complete(),
gmm_imputation(),
gmm_impute(),
mechanism,
proxy_fmi(),
proxy_mnar_sensitivity(),
proxy_pool()
Examples
set.seed(1)
x1 <- rnorm(150); x2 <- x1 + rnorm(150)
x2[runif(150) < 0.3] <- NA
imp <- gmm_impute(cbind(x1, x2), N = 1L, m = 10L, seed = 1L)
if (requireNamespace("mice", quietly = TRUE)) {
fit <- with(as_mids(imp), lm(x2 ~ x1))
summary(mice::pool(fit))
}
#> term estimate std.error statistic df p.value
#> 1 (Intercept) 0.01909702 0.09597906 0.1989707 71.05456 8.428539e-01
#> 2 x1 0.89798425 0.09967653 9.0089838 111.29150 6.668483e-15