residualDiagnostics.merMod: residualDiagnostics methods for merMod objects

In multilevelTools: Multilevel and Mixed Effects Model Diagnostics and Effect Sizes

Description

residualDiagnostics methods for merMod objects

Usage

## S3 method for class 'merMod'
residualDiagnostics(
  object,
  ev.perc = 0.001,
  robust = FALSE,
  distr = "normal",
  standardized = TRUE,
  ...
)

Arguments

object	An object with class merMod. Currently only lmer() models are supported.
ev.perc	The extreme value percentile to use. Defaults to .001.
robust	A logical value, whether to use robust estimates or not. Defaults to FALSE.
distr	A character string specifying the assumed distribution. Currently “normal”, but may expand in the future if glmer() models are supported.
standardized	A logical value whether to use standardized residual values or not. Defaults to TRUE.
...	Additional arguments. Not currently used.

Value

A logical (is.residualDiagnostics) or a residualDiagnostics object (list) for as.residualDiagnostics and residualDiagnostics.

Examples

library(JWileymisc)
sleep[1,1] <- NA
m <- lme4::lmer(extra ~ group + (1 | ID), data = sleep)

residualDiagnostics(m)$Residuals

#  gm1 <- lme4::glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
#    data = lme4::cbpp, family = binomial)
# residualDiagnostics(gm1) ## should be an error

rm(m, sleep)

multilevelTools documentation built on March 13, 2020, 2:07 a.m.