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Last data update: 2014.03.03

R: Plots a binary response variable versus a quantitative...

plotBinResp

R Documentation

Plots a binary response variable versus a quantitative explanatory variable.

Description

A function to plot a binary response variable versus a quantitative explanatory variable.

Usage

plotBinResp(x, ...)

## Default S3 method:
plotBinResp(x, y, xlab = paste(deparse(substitute(x))),
  ylab = paste(deparse(substitute(y))), plot.pts = TRUE, col.pt = "black",
  transparency = NULL, plot.p = TRUE, breaks = 25, p.col = "blue",
  p.pch = 3, p.cex = 1.25, yaxis1.ticks = seq(0, 1, 0.1),
  yaxis1.lbls = c(0, 0.5, 1), yaxis2.show = TRUE, ...)

## S3 method for class 'formula'
plotBinResp(x, data = NULL, xlab = names(mf)[2],
  ylab = names(mf)[1], ...)

Arguments

`x`	A quantitative explanatory variable or a formula of the form `factor~quant`.
`y`	A binary response variable.
`xlab`	A string for labelling the x-axis.
`ylab`	A string for labelling the y-axis.
`plot.pts`	A logical that indicates (`TRUE` (default)) whether the points should be plotted (`TRUE`; default) or not (`FALSE`).
`col.pt`	A string used to indicate the color of the plotted points. Will be transparent unless `transparency=1`.
`transparency`	A numeric that indicates how many points would be plotted on top of each other before the ‘point’ would have the full `col.pt` color. The reciprocal of this value is the alpha transparency value.
`plot.p`	A logical that indicates if the proportion for categorized values of X are plotted (`TRUE`; default).
`breaks`	A number that indicates how many intervals over which to compute proportions or a numeric vector that contains the endpoints of the intervals over which to compute proportions if `plot.p=TRUE`.
`p.col`	A color to plot the proportions.
`p.pch`	A plotting character for plotting the proportions.
`p.cex`	A character expansion factor for plotting the proportions.
`yaxis1.ticks`	A numeric vector that indicates where tick marks should be placed on the left y-axis (for the proportion of ‘successes’).
`yaxis1.lbls`	A numeric vector that indicates labels for the tick marks on the left y-axis (for the proportion of ‘successes’).
`yaxis2.show`	A logical that indicates whether the right y-axis should be created (`=TRUE`; default) or not.
`data`	The data frame from which the formula should be evaluated.
`...`	Other arguments to be passed to the plot functions.

Details

This function produces a plot that can be used to visualize the density of points for a binary response variable as a function of a quantitative explanatory variable. In addition, the proportion of “1”s for the response variable at various “levels” of the explanatory variable are shown.

Value

None. However, a plot is produced.

Note

This function is meant to allow newbie students the ability to visualize the data corresponding to a binary logistic regression without getting “bogged-down” in the gritty details of how to produce this plot.

Author(s)

Derek H. Ogle, derek@derekogle.com

Examples

## NASA space shuttle o-ring failures -- from graphics package
fail <- factor(c(2,2,2,2,1,1,1,1,1,1,2,1,2,1,1,1,1,2,1,1,1,1,1),
levels = 1:2, labels = c("no","yes"))
temperature <- c(53,57,58,63,66,67,67,67,68,69,70,70,70,70,72,73,75,75,76,76,78,79,81)
d <- data.frame(fail,temperature)

## Default plot (using formula notation)
plotBinResp(fail~temperature,data=d)

## Controlling where proportions are computed with a sequence in breaks
plotBinResp(fail~temperature,data=d,breaks=seq(50,85,5))

## Controlling where proportions are computed with an integer in breaks
plotBinResp(fail~temperature,data=d,breaks=10)

## Controlling where proportions are computed at each value of x
plotBinResp(fail~temperature,data=d,breaks=NULL)

## Don't plot points, just plot proportions
plotBinResp(fail~temperature,data=d,plot.pts=FALSE)

## Don't plot proportions, just plot points
plotBinResp(fail~temperature,data=d,plot.p=FALSE)

## Change points colors, and eliminate transparency
plotBinResp(fail~temperature,data=d,col.pt="red",transparency=1)

## Remove the right y-axis
plotBinResp(fail~temperature,data=d,yaxis2.show=FALSE)

## Change left y-axis ticks
plotBinResp(fail~temperature,data=d,yaxis1.ticks=c(0,1),yaxis1.lbls=c(0,1))

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(FSA)


 ############################################
 ##      FSA package, version 0.8.7        ##
 ##    Derek H. Ogle, Northland College    ##
 ##                                        ##
 ## Run ?FSA for documentation.            ##
 ## Run citation('FSA') for citation ...   ##
 ##   please cite if used in publication.  ##
 ##                                        ##
 ## See derekogle.com/fishR/ for more      ##
 ##   thorough analytical vignettes.       ##
 ############################################


> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/FSA/plotBinResp.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotBinResp
> ### Title: Plots a binary response variable versus a quantitative
> ###   explanatory variable.
> ### Aliases: plotBinResp plotBinResp.default plotBinResp.formula
> ### Keywords: hplot models
> 
> ### ** Examples
> 
> ## NASA space shuttle o-ring failures -- from graphics package
> fail <- factor(c(2,2,2,2,1,1,1,1,1,1,2,1,2,1,1,1,1,2,1,1,1,1,1),
+ levels = 1:2, labels = c("no","yes"))
> temperature <- c(53,57,58,63,66,67,67,67,68,69,70,70,70,70,72,73,75,75,76,76,78,79,81)
> d <- data.frame(fail,temperature)
> 
> ## Default plot (using formula notation)
> plotBinResp(fail~temperature,data=d)
> 
> ## Controlling where proportions are computed with a sequence in breaks
> plotBinResp(fail~temperature,data=d,breaks=seq(50,85,5))
> 
> ## Controlling where proportions are computed with an integer in breaks
> plotBinResp(fail~temperature,data=d,breaks=10)
> 
> ## Controlling where proportions are computed at each value of x
> plotBinResp(fail~temperature,data=d,breaks=NULL)
> 
> ## Don't plot points, just plot proportions
> plotBinResp(fail~temperature,data=d,plot.pts=FALSE)
> 
> ## Don't plot proportions, just plot points
> plotBinResp(fail~temperature,data=d,plot.p=FALSE)
> 
> ## Change points colors, and eliminate transparency
> plotBinResp(fail~temperature,data=d,col.pt="red",transparency=1)
> 
> ## Remove the right y-axis
> plotBinResp(fail~temperature,data=d,yaxis2.show=FALSE)
> 
> ## Change left y-axis ticks
> plotBinResp(fail~temperature,data=d,yaxis1.ticks=c(0,1),yaxis1.lbls=c(0,1))
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>