merTools (version 0.6.2)

lmerModList: Apply a multilevel model to a list of data frames

Description

Apply a multilevel model to a list of data frames

Apply a Bayesian multilevel model to a list of data frames

Apply a generalized linear multilevel model to a list of data frames

Apply a Bayesian generalized linear multilevel model to a list of data frames

Usage

lmerModList(formula, data, parallel = FALSE, ...)
blmerModList(formula, data, parallel = FALSE, ...)
glmerModList(formula, data, parallel = FALSE, ...)
bglmerModList(formula, data, parallel = FALSE, ...)

Value

a list of fitted merMod objects of class merModList

a merModList

a merModList

a merModList

Arguments

formula

a formula to pass through compatible with merMod

data

a list object with each element being a data.frame

parallel

logical, should the models be run in parallel? Default FALSE. If so, the `future_lapply` function from the `future.apply` package is used. See details.

...

additional arguments to pass to the estimating function

Details

Parallel computing is provided by the `futures` package, and its extension the `future.apply` package to provide the `future_lapply` function for easy parallel computations on lists. To use this package, simply register a parallel backend using the `plan()` function from `futures` - an example is to use `plan(multisession)`

Examples

# \donttest{
sim_list <- replicate(n = 10,
        expr = sleepstudy[sample(row.names(sleepstudy), 180),],
        simplify=FALSE)
fml <- "Reaction ~ Days + (Days | Subject)"
mod <- lmerModList(fml, data = sim_list)
summary(mod)
# }