ggPredict: Visualize predictions from the multiple regression models.

In cardiomoon/ggiraphExtra: Make Interactive 'ggplot2'. Extension to 'ggplot2' and 'ggiraph'

Description

Visualize predictions from the multiple regression models.

Usage

ggPredict(
  fit,
  colorn = 4,
  point = NULL,
  jitter = NULL,
  se = FALSE,
  show.summary = FALSE,
  colorAsFactor = FALSE,
  digits = 2,
  interactive = FALSE,
  ...
)

Arguments

fit	a model object for which prediction is desired.
colorn	Integer. Number of subgroups of color variables.
point	Logical. Whether or not draw each point
jitter	Logical. Whether or not jitter points
se	Logical. Whether or not draw se
show.summary	Logical. Whether or not show summary
colorAsFactor	Logical. Whether or not treat color variable as categorical variable
digits	An integer indicating the number of decimal places
interactive	A logical value. If TRUE, an interactive plot will be returned
...	additional arguments affecting the predictions produced.

Examples

require(moonBook)
require(ggplot2)
require(ggiraph)
require(plyr)
fit=lm(NTAV~age*weight,data=radial)
fit=lm(NTAV~age*weight*DM,data=radial)
fit=lm(NTAV~age+DM,data=radial)
ggPredict(fit,interactive=TRUE)
require(TH.data)
fit=glm(cens~pnodes*horTh,data=GBSG2,family=binomial)
ggPredict(fit,se=TRUE)
fit1=glm(cens~pnodes*age,data=GBSG2,family=binomial)
ggPredict(fit1)
ggPredict(fit1,colorn=100,jitter=FALSE,interactive=TRUE)
fit2=glm(cens~pnodes*age*horTh,data=GBSG2,family=binomial)
ggPredict(fit2,colorn=100,jitter=FALSE,interactive=TRUE)

cardiomoon/ggiraphExtra documentation built on Oct. 9, 2020, 4:16 a.m.