HLMdiag (version 0.5.0)

dotplot_diag: Dot plots for influence diagnostics

Description

This is a function that can be used to create (modified) dotplots for the diagnostic measures. The plot allows the user to understand the distribution of the diagnostic measure and visually identify unusual cases.

Usage

dotplot_diag(
  x,
  cutoff,
  name = c("cooks.distance", "mdffits", "covratio", "covtrace", "rvc", "leverage"),
  data,
  index = NULL,
  modify = FALSE,
  ...
)

Arguments

x

values of the diagnostic of interest

cutoff

value(s) specifying the boundary for unusual values of the diagnostic. The cutoff(s) can either be supplied by the user, or automatically calculated using measures of internal scaling if cutoff = "internal".

name

what diagnostic is being plotted (one of "cooks.distance", "mdffits", "covratio", "covtrace", "rvc", or "leverage"). This is used for the calculation of "internal" cutoffs.

data

data frame to use (optional)

index

optional parameter to specify index (IDs) of x values. If NULL(default), values will be indexed in the order of the vector passed to x.

modify

specifies the geom to be used to produce a space-saving modification: either "dotplot" or "boxplot"

...

other arguments to be passed to ggplot()

Examples

# NOT RUN {
data(sleepstudy, package = 'lme4')
fm <- lme4::lmer(Reaction ~ Days + (Days | Subject), sleepstudy)

#Observation level deletion and diagnostics
obs.infl <- hlm_influence(fm, level = 1)

dotplot_diag(x = obs.infl$cooksd, cutoff = "internal", name = "cooks.distance", modify = FALSE)

dotplot_diag(x = obs.infl$mdffits, cutoff = "internal", name = "cooks.distance", modify = FALSE)

# Subject level deletion and diagnostics
subject.infl  <- hlm_influence(fm, level = "Subject")

dotplot_diag(x = subject.infl$cooksd, cutoff = "internal",
             name = "cooks.distance", modify = FALSE)
             
dotplot_diag(x = subject.infl$mdffits, cutoff = "internal", name = "mdffits", modify = "dotplot")
# }