ggEffect.lm: Visualize the effect of interaction between two continuous...

In cardiomoon/moonBook2: Functions and Datasets for the 2nd Book by Keon-Woong Moon

Description

Visualize the effect of interaction between two continuous independent variables on a response variable

Usage

## S3 method for class 'lm'
ggEffect(x, no = 1, probs = c(0.1, 0.5, 0.9), point = TRUE,
  xvalue = NULL, digits = 2, use.rownames = FALSE, interactive = FALSE)

Arguments

x	An integer(1 or 2) indicating which independent variable is used as x-axis variable
probs	A vector of probability weights for obtaining the elements of the vector being sampled.Default value is c(0.10,0.5,0.90)
point	A logical value. If TRUE, draw points
xvalue	A numeric vector
digits	An integer indicating the number of decimal places
use.rownames	If TRUE, use rownames in label
interactive	A logical value. If TRUE, an interactive plot will be returned

Value

An interactive plot showing interaction

Examples

data(mtcars)
fit=lm(mpg~wt*hp,data=mtcars)
require(ggplot2)
ggEffect(fit,use.rownames=TRUE)
ggEffect(fit,use.rownames=TRUE,interactive=TRUE)
ggEffect(fit,no=2)
require(moonBook)
fit2=lm(NTAV~age*smoking,data=radial)
ggEffect(fit2,interactive=TRUE)
fit3=lm(age~sex*smoking,data=acs)
ggEffect(fit3,interactive=TRUE)

cardiomoon/moonBook2 documentation built on May 13, 2019, 12:40 p.m.