modelPlot {autoReg}

Draw coefficients/odds ratio/hazard ratio plot

Description

Draw coefficients/odds ratio/hazard ratio plot

Usage

modelPlot(
  fit,
  widths = NULL,
  change.pointsize = TRUE,
  show.OR = TRUE,
  show.ref = TRUE,
  bw = TRUE,
  legend.position = "top",
  ...
)

Arguments

fit

An object of class glm

widths

Numeric vector

change.pointsize

logical Whether or not change point size

show.OR

logical Whether or not show odds ratio

show.ref

logical Whether or not show reference

bw

logical If true, use grey scale

legend.position

legend position default value is 'top'

...

Further arguments to be passed to autoReg()

Value

modelPlot returns an object of class "modelPlot" An object of class modelPlot is a list containing at least of the following components:

tab1

The first table containing names

tab2

The 2nd table containing levels

tab3

The 3rd table containing coefficients or odds ratio or hazards ratio

p

A ggplot

widths

the widths of the tables and the ggplot

Examples

fit=lm(mpg~wt*hp+am,data=mtcars)
modelPlot(fit,widths=c(1,0,2,3))
modelPlot(fit,uni=TRUE,threshold=1,widths=c(1,0,2,3))
fit=lm(Sepal.Width~Sepal.Length*Species,data=iris)
modelPlot(fit)
modelPlot(fit,uni=TRUE,change.pointsize=FALSE)

data(cancer,package="survival")
fit=glm(status~rx+age+sex+nodes+obstruct+perfor,data=colon,family="binomial")
modelPlot(fit)
modelPlot(fit,uni=TRUE,multi=TRUE,threshold=1)
modelPlot(fit,multi=TRUE,imputed=TRUE,change.pointsize=FALSE)
data(colon_s,package="finalfit")
fit=glm(mort_5yr~age.factor+sex.factor+obstruct.factor+perfor.factor,data=colon_s,family="binomial")
modelPlot(fit)
modelPlot(fit,uni=TRUE,multi=TRUE,threshold=1)
modelPlot(fit,uni=TRUE,multi=TRUE)
modelPlot(fit,uni=TRUE,multi=TRUE,threshold=1,show.ref=FALSE)
library(survival)
fit=coxph(Surv(time,status)~rx+age+sex+obstruct+perfor,data=colon)
modelPlot(fit)
modelPlot(fit,uni=TRUE,threshold=1)
modelPlot(fit,multi=FALSE,final=TRUE,threshold=1)
fit=coxph(Surv(time,status)~age.factor+sex.factor+obstruct.factor+perfor.factor,data=colon_s)
modelPlot(fit)
modelPlot(fit,uni=TRUE,threshold=1)
modelPlot(fit,uni=TRUE,threshold=1,show.ref=FALSE)
modelPlot(fit,imputed=TRUE)