lmerTest (version 3.1-3)

plot.step_list: Plot LS-means for Backward Reduced Model

Description

Computes the LS-means for the final backward reduced model and passes these to plot.ls_means.

Usage

# S3 method for step_list
plot(
  x,
  y = NULL,
  which = NULL,
  pairwise = FALSE,
  mult = TRUE,
  level = 0.95,
  ddf = c("Satterthwaite", "Kenward-Roger"),
  ...
)

Arguments

x

a step_list object; the result of running step.

y

not used and ignored with a warning.

which

optional character vector naming factors for which LS-means should be plotted. If NULL (default) plots for all LS-means are generated.

pairwise

pairwise differences of LS-means?

mult

if TRUE and there is more than one term for which to plot LS-means the plots are organized in panels with facet_wrap.

level

confidence level.

ddf

denominator degree of freedom method.

...

currently not used.

Details

Error bars are confidence intervals - the default is 95 level can be changed.

See Also

ls_means and plot.ls_means

Examples

# NOT RUN {
# }
# NOT RUN {
# Fit example model:
tv <- lmer(Sharpnessofmovement ~ TVset * Picture +
             (1 | Assessor:TVset) + (1 | Assessor:Picture) +
             (1 | Assessor:Picture:TVset) + (1 | Repeat) + (1 | Repeat:Picture) +
             (1 | Repeat:TVset) + (1 | Repeat:TVset:Picture) + (1 | Assessor),
           data = TVbo)

# Backward reduce the model:
(st <- step(tv)) # takes ~10 sec to run

# Pairwise comparisons of LS-means for Picture and TVset:
  plot(st, which=c("Picture", "TVset"), pairwise = TRUE)
# }
# NOT RUN {
# }