Usage
sjp.resid(fit, geom.size = 2, remove.estimates = NULL, show.lines = TRUE, show.resid = TRUE, show.pred = TRUE, show.ci = F, prnt.plot = TRUE)
Arguments
fit
fitted linear (mixed) regression model (including objects of class
gls
or plm
). 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.
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.
show.lines
logical, if TRUE
, a line connecting predicted and
residual values is plotted. Set this argument to FALSE
, if
plot-building is too time consuming.
show.resid
logical, if TRUE
, residual values are plotted.
show.pred
logical, if TRUE
, predicted values are plotted.
show.ci
logical, if TRUE
, depending on type
, a confidence
interval or region is added to the plot.
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.