ggEffect: ggEffect generic

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

ggEffect(x, ...)

## Default S3 method:
ggEffect(x, y, x1, x2, ...)

## S3 method for class 'formula'
ggEffect(x, data, ...)

Arguments

x	Object to ggEffect
...	additional arguments passed to the generic function
x1	A name of one of the independent variable
x2	A name of the other independent variable
data	A data
x	A name of response variable
x	A formula

Value

An interactive plot showing interaction

Methods (by class)

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

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

Examples

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

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