stat_fit_tb.Rd
stat_fit_tb
fits a model and returns a "tidy" version of
the model's summary or ANOVA table, using package 'broom'. The annotation
is added to the plots in tabular form.
stat_fit_tb(mapping = NULL, data = NULL, geom = "table_npc", method = "lm", method.args = list(formula = y ~ x), tb.type = "fit.summary", tb.vars = NULL, digits = 3, label.x = "center", label.y = "top", label.x.npc = NULL, label.y.npc = NULL, position = "identity", na.rm = FALSE, show.legend = FALSE, inherit.aes = TRUE, ...)
mapping  The aesthetic mapping, usually constructed with


data  A layer specific dataset  only needed if you want to override the plot defaults. 
geom  The geometric object to use display the data 
method  character. 
method.args  list of arguments to pass to 
tb.type  character One of "fit.summary", "fit.anova" or "fit.coefs". 
tb.vars  character vector, optionally named, used to select and or rename the columns of the table returned. 
digits  integer indicating the number of significant digits to be used. 
label.x, label.y 

label.x.npc, label.y.npc 

position  The position adjustment to use for overlapping points on this layer 
na.rm  a logical indicating whether NA values should be stripped before the computation proceeds. 
show.legend  logical. Should this layer be included in the legends?

inherit.aes  If 
...  other arguments passed on to 
The output of tidy
is
returned as a single "cell" in a tibble (i.e. a tibble nested within a
tibble). The returned data
object contains a single, containing the
result from a single model fit to all data in a panel. If grouping is
present, it is ignored.
tidy
for details on how the tidying of the
resulst of model fits is done. See geom_table
for details
on how the formating and location of the table can be adjusted.
library(ggplot2) # ttest example x < c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1) group < factor(c(rep("A", 4), rep("B", 5))) my.df < data.frame(x, group) ggplot(my.df, aes(group, x)) + geom_point() + stat_fit_tb(method = "t.test", tb.vars = c("italic(t)" = "estimate", "italic(P)" = "p.value"), parse = TRUE)