ez.scatterplot2 | R Documentation |
scatter plot with ggplot
ez.scatterplot2(
df,
cmd,
rp.size = 5,
rp.x = 0.25,
rp.y = 0.99,
colors = ez.palette("Zhu"),
shapes = c(16, 17, 15, 3, 7, 8),
line.color = "#BE1B22",
point.color = "#0086B8",
point.shape = 16,
point.alpha = 0.95,
point.size = 3,
rug.size = 0.25,
ylab = NULL,
xlab = NULL,
zlab = NULL,
legend.position = "top",
legend.direction = "horizontal",
legend.box = T,
legend.size = c(0, 10),
rp = TRUE,
se = TRUE,
rug = FALSE,
ellipse = FALSE,
theme.apa = TRUE
)
df |
data frame |
cmd |
like "y~x+a+b", "y~x+a+b|z", "y~x+a+b||z", "y~x+a+b|||z"where y x are continous, z discrete (| one regression line, || multiple regression lines by levels of z–gives interaction p value), +a+b optional for covariates residualization
|
rp.size |
r p values font size, ignored if rp=FALSE |
rp.x |
r p values x position (0-1, relative to top left, big–>right), ignored if rp=FALSE. Internally, convert to geom_label(x,y) where x,y refers to actually x,y axis value |
rp.y |
r p values y position (0-1, relative to top left, big–>bottom), ignored if rp=FALSE |
line.color |
only applicable when y~x and y~x|z (ie, not auto varied with aes()), regression line color |
point.color |
only applicable when y~x (ie, not auto varied with aes()). for auto ones, use scale_*_* |
point.shape |
only applicable when y~x (ie, not auto varied with aes()). for auto ones, use scale_*_* |
point.alpha |
if overplot for points, reduce alpha |
point.size |
if less point, increase size |
rug.size |
rug size |
ylab |
y label NULL |
xlab |
x label NULL |
zlab |
z/fill/legend label, only applicable when there is z provided NULL |
legend.position |
legend position 'top', 'bottom', 'left', 'right', 'none', c(x,y,two-element numeric vector)
|
legend.direction |
horizontal or vertical |
legend.box |
box of legend, T or F |
legend.size |
c(0,10) the first number 0 controls the legend title, 0=hide; the second number controls legend.key.size, legend.text |
rp |
show r (signed) and p values |
se |
standard error of linear regression line |
rug |
marginal rug indicating univariate distribution |
ellipse |
draw confidence ellipses, powered by stat_ellipse() |
a ggplot object (+theme_apa() to get apa format plot)
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