Unlimited learning, half price | 50% off
Get 50% off unlimited learning
Learn R Programming
lava (version 1.4.1)

plotConf: Plot regression lines

Description

Plot regression line (with interactions) and partial residuals.

Usage

plotConf(model, var1 = all.vars(formula(model))[2], var2 = NULL,
  data = NULL, ci.lty = 0, ci = TRUE, level = 0.95, pch = 16,
  lty = 1, lwd = 2, npoints = 100, xlim, col = NULL, colpt,
  alpha = 0.5, cex = 1, delta = 0.07, centermark = 0.03, jitter = 0.2,
  cidiff = FALSE, mean = TRUE, legend = ifelse(is.null(var1), FALSE,
  "topright"), trans = function(x) {     x }, partres = inherits(model,
  "lm"), partse = FALSE, labels, vcov, predictfun, plot = TRUE,
  new = TRUE, ...)

Arguments

model
Model object (e.g. lm)
var1
predictor (Continuous or factor)
var2
Factor that interacts with var1
data
data.frame to use for prediction (model.frame is used as default)
ci.lty
Line type for confidence limits
ci
Boolean indicating wether to draw pointwise 95% confidence limits
level
Level of confidence limits (default 95%)
pch
Point type for partial residuals
lty
Line type for estimated regression lines
lwd
Line width for regression lines
npoints
Number of points used to plot curves
xlim
Range of x axis
col
Color (for each level in var2)
colpt
Color of partial residual points
alpha
Alpha level
cex
Point size
delta
For categorical var1
centermark
For categorical var1
jitter
For categorical var1
cidiff
For categorical var1
mean
For categorical var1
legend
Boolean (add legend)
trans
Transform estimates (e.g. exponential)
partres
Boolean indicating whether to plot partial residuals
partse
.
labels
Optional labels of var2
vcov
Optional variance estimates
predictfun
Optional predict-function used to calculate confidence limits and predictions
plot
If FALSE return only predictions and confidence bands
new
If FALSE add to current plot
...
additional arguments to lower level functions

Value

  • list with following members:
  • xVariable on the x-axis (var1)
  • yVariable on the y-axis (partial residuals)
  • predictMatrix with confidence limits and predicted values

See Also

termplot

Examples

Run this code
n <- 100
x0 <- rnorm(n)
x1 <- seq(-3,3, length.out=n)
x2 <- factor(rep(c(1,2),each=n/2), labels=c("A","B"))
y <- 5 + 2*x0 + 0.5*x1 + -1*(x2=="B")*x1 + 0.5*(x2=="B") + rnorm(n, sd=0.25)
dd <- data.frame(y=y, x1=x1, x2=x2)
lm0 <- lm(y ~ x0 + x1*x2, dd)
plotConf(lm0, var1="x1", var2="x2")
abline(a=5,b=0.5,col="red")
abline(a=5.5,b=-0.5,col="red")
### points(5+0.5*x1 -1*(x2=="B")*x1 + 0.5*(x2=="B") ~ x1, cex=2)

data(iris)
l <- lm(Sepal.Length ~ Sepal.Width*Species,iris)
plotConf(l,var2="Species")

Run the code above in your browser using DataLab