The `bootmlm`

package does bootstrap resampling for multilevel models.
Currently only models fitted with `lme4::lmer()`

is supported. It's still in
developmental stage and is not yet on CRAN. However, you can install the package
on GitHub:

```
if (!require("devtools")) {
install.packages("devtools")
}
devtools::install_github("marklhc/bootmlm")
```

Here is an example to get the bootstrap distributions of the fixed effects and the level-1 error SD:

```
library(lme4)
fm01ML <- lmer(Yield ~ (1 | Batch), Dyestuff, REML = FALSE)
mySumm <- function(x) {
c(getME(x, "beta"), sigma(x))
}
# Covariance preserving residual bootstrap
library(bootmlm)
boo01 <- bootstrap_mer(fm01ML, mySumm, type = "residual", nsim = 100)
# Plot bootstrap distribution of fixed effect
library(boot)
plot(boo01, index = 1)
# Get confidence interval
boot.ci(boo01, index = 2, type = c("norm", "basic", "perc"))
# BCa using influence values computed from `empinf_mer`
boot.ci(boo01, index = 2, type = "bca", L = empinf_mer(fm01ML, mySumm, 2))
```

marklhc/bootmlm documentation built on April 20, 2018, 2:35 a.m.

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