residualDiagnostics methods for merMod objects

Usage

# S3 method for 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
#>        Residuals  Predicted   isEV Index
#>            <num>      <num> <fctr> <int>
#>  1: -0.700128956 -0.9621661     No     2
#>  2:  0.021690939 -0.2197610     No     3
#>  3: -0.117254135 -1.0931787     No     4
#>  4:  0.658754382 -0.7001407     No     5
#>  5:  0.665701421  2.7935304     No     6
#>  6:  0.323896367  3.4049228     No     7
#>  7:  0.400316373  0.4353024     No     8
#>  8: -1.532410421  1.3960619     No     9
#>  9:  0.279434030  1.7454290     No    10
#> 10: -0.106066615  1.9966292     No    11
#> 11:  0.165396845  0.6493196     No    12
#> 12: -0.320216425  1.3917247     No    13
#> 13: -0.459161498  0.5183069     No    14
#> 14: -1.110119449  0.9113449     No    15
#> 15: -0.005505897  4.4050160     No    16
#> 16:  0.530822260  5.0164084     No    17
#> 17: -0.490424247  2.0467880     No    18
#> 18:  1.747981709  3.0075476     No    19
#> 19:  0.047293317  3.3569147     No    20

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

rm(m, sleep)