Usage
sjp.lmer(fit, type = "re", vars = NULL, ri.nr = NULL, group.estimates = NULL, remove.estimates = NULL, emph.grp = NULL, sample.n = NULL, poly.term = NULL, sort.est = NULL, title = NULL, legend.title = NULL, axis.labels = NULL, axis.title = NULL, geom.size = NULL, geom.colors = "Set1", show.values = TRUE, show.p = TRUE, show.ci = FALSE, show.legend = FALSE, show.loess = FALSE, show.loess.ci = FALSE, show.intercept = FALSE, string.interc = "(Intercept)", p.kr = TRUE, point.alpha = 0.2, scatter.plot = TRUE, fade.ns = FALSE, axis.lim = NULL, digits = 2, vline.type = 2, vline.color = "grey70", facet.grid = TRUE, free.scale = FALSE, y.offset = 0.1, prnt.plot = TRUE, ...)
Arguments
fit
a fitted model as returned by the lmer-function. type
type of plot. Use one of following:
vars
numeric vector with column indices of selected variables or a character vector with
variable names of selected variables from the fitted model, which should be used to plot
estimates, fixed effects slopes (for lmer) or probability or
incidents curves
(for glmer) of random intercepts. ri.nr
numeric vector. If type = "re" or type = "ri.slope",
and fitted model has more than one random intercept, ri.nr indicates
which random effects of which random intercept (or: which list elements
of ranef) will be plotted. Default is NULL,
so all random effects will be plotted. group.estimates
numeric or character vector, indicating a group identifier for
each estimate. Dots and confidence intervals of estimates are coloured
according to their group association. See 'Examples'.
remove.estimates
character vector with coefficient names that indicate
which estimates should be removed from the plot.
remove.estimates = "est_name" would remove the estimate est_name. Default
is NULL, i.e. all estimates are printed.
emph.grp
numeric vector with index numbers of grouping levels (from random effect).
If type = "ri.slope" and facet.grid = FALSE,
an integrated plot of predicted probabilities of fixed effects resp. fixed
effects slopes for each grouping level is plotted. To better find
certain groups, use this argument to emphasize these groups in the plot.
See 'Examples'.
sample.n
numeric vector. only applies, if type = "rs.ri". If
plot has many random intercepts (grouping levels), overplotting of
regression lines may occur. In this case, consider random sampling of
grouping levels. If sample.n is of length 1, a random sample
of sample.n observation is selected to plot random intercepts.
If sample.n is of length > 1, random effects indicated by
the values in sample.n are selected to plot random effects.
Use the latter option to always select a fixed, identical set of
random effects for plotting (useful when ecomparing multiple models).
poly.term
name of a polynomial term in fit as string. Needs to be
specified, if type = "poly", in order to plot marginal effects
for polynomial terms. See 'Examples'.
sort.est
determines in which way estimates are sorted in the plot:
- If
NULL (default), no sorting is done and estimates are sorted in order of model coefficients.
- If
sort.est = "sort.all", estimates are re-sorted for each coefficient (only applies if type = "re" and facet.grid = FALSE), i.e. the estimates of the random effects for each predictor are sorted and plotted to an own plot.
- If
type = "fe" or type = "fe.std", TRUE will sort estimates
- If
type = "re", specify a predictor's / coefficient's name to sort estimates according to this coefficient.
See 'Examples'.
title
character vector with one or more labels that are used as plot title.
legend.title
character vector, used as title for the plot legend. Note that
only some plot types have legends (e.g. type = "pred" or when
grouping estimates with group.estimates).
axis.labels
character vector with labels for the model terms, used as axis labels.
For mixed models, should either be vector of fixed effects variable labels
(if type = "fe" or type = "fe.std") or a vector of group (value)
labels from the random intercept's categories (if type = "re").
axis.title
character vector of length one or two (depending on
the plot function and type), used as title(s) for the x and y axis.
If not specified, a default labelling is chosen.
geom.size
size resp. width of the geoms (bar width, line thickness or point size,
depending on plot type and function). Note that bar and bin widths mostly
need smaller values than dot sizes.
geom.colors
user defined color palette for geoms. If group.estimates
is not specified, must either be vector with two color values or a specific
color palette code (see 'Details' in sjp.grpfrq). Else, if
group.estimates is specified, geom.colors must be a vector
of same length as groups. See 'Examples'. show.values
logical, whether values should be plotted or not.
show.p
logical, adds significance levels to values, or value and
variable labels.
show.ci
logical, if TRUE, depending on type, a confidence
interval or region is added to the plot.
show.legend
logical, if TRUE, and depending on plot type and
function, a legend is added to the plot.
show.loess
logical, if TRUE, and depending on type, an
additional loess-smoothed line is plotted.
show.loess.ci
logical, if TRUE, a confidence region for the loess-smoothed line
will be plotted. Default is FALSE. Only applies, if show.loess = TRUE
(and for sjp.lmer, only applies if type = "fe.slope"
or type = "fe.resid"). show.intercept
logical, if TRUE, the intercept of the fitted model is also plotted.
Default is FALSE. For glm's, please note that due to exponential
transformation of estimates, the intercept in some cases can not be calculated, thus the
function call is interrupted and no plot printed.
string.interc
string, axis label of intercept estimate. Only applies,
if show.intercept = TRUE and axis.labels is not NULL.
p.kr
logical, if TRUE, p-value estimation is based on conditional
F-tests with Kenward-Roger approximation for the df. Caution: Computation
may take very long time for large samples!
point.alpha
alpha value of point-geoms in the scatter plots.
scatter.plot
logical, if TRUE (default), a scatter plot of
response and predictor values for each predictor of the model
is plotted. Only applies for slope-type plots.
fade.ns
if TRUE, non significant estimates will be printed in slightly faded colors.
axis.lim
numeric vector of length 2, defining the range of the plot axis.
Depending on plot type, may effect either x- or y-axis, or both.
For multiple plot outputs (e.g., from type = "eff" or
type = "slope" in sjp.glm), axis.lim may
also be a list of vectors of length 2, defining axis limits for each
plot (only if non-faceted). digits
numeric, amount of digits after decimal point when rounding estimates and values.
vline.type
linetype of the vertical "zero point" line. Default is 2 (dashed line).
vline.color
color of the vertical "zero point" line. Default value is "grey70".
facet.grid
TRUE to arrange the lay out of of multiple plots
in a grid of an integrated single plot. This argument calls
facet_wrap or facet_grid
to arrange plots. Use plot_grid to plot multiple plot-objects
as an arranged grid with grid.arrange.free.scale
if TRUE and facet.grid = TRUE, each facet grid
gets its own fitted scale. If free.scale = FALSE, each facet in
the grid has the same scale range.
y.offset
numeric, offset for text labels when their alignment is adjusted
to the top/bottom of the geom (see hjust and vjust).
prnt.plot
logical, if TRUE (default), plots the results as graph. Use FALSE if you don't
want to plot any graphs. In either case, the ggplot-object will be returned as value.
...
other arguments, passed down to the effect resp.
allEffects function when type = "eff".