Plot the impact of grouping-factor levels on predictions

Plot the output of one or more REimpact calls on a single chart. Each point is the weighted-average fitted value for a bin of the expected-rank distribution of a grouping factor, with a confidence interval derived from the weighted standard error. Supplying a named list of REimpact results overlays them on the same axes – for example to compare the influence of two different grouping factors, or the same factor across two models – which previously required hand-assembling the data frames (#84).

Usage

plotREimpact(data, level = 0.95, facet = TRUE, point_size = 2.5)

Arguments

data

either a single data.frame produced by REimpact, or a named list of such data.frames. When a named list is supplied the names are used to colour and label the series.

level

the width of the confidence interval (default 0.95).

facet

logical, facet the plot by case (default TRUE).

point_size

numeric size of the plotted central points.

Value

a ggplot2 object.

See also

REimpact

Examples

# \donttest{
 m1 <- lmer(Reaction ~ Days + (1 | Subject), sleepstudy)
 imp <- REimpact(m1, newdata = sleepstudy[1, ], groupFctr = "Subject",
                 breaks = 4)
 plotREimpact(imp)


 # Compare two grouping factors on the same chart
 g1 <- lmer(y ~ lectage + studage + (1 | d) + (1 | s), data = InstEval)
 d_eff <- REimpact(g1, newdata = InstEval[1, ], groupFctr = "d", breaks = 4)
 s_eff <- REimpact(g1, newdata = InstEval[1, ], groupFctr = "s", breaks = 4)
 plotREimpact(list("Instructor (d)" = d_eff, "Student (s)" = s_eff))

 # }