plotBinResp {FSA} | R Documentation |

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

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], ...)

`x` |
A quantitative explanatory variable or a formula of the form |

`...` |
Other arguments to be passed to the plot functions. |

`y` |
A binary response variable. |

`xlab` |
A string for labeling the x-axis. |

`ylab` |
A string for labeling the y-axis. |

`plot.pts` |
A logical that indicates ( |

`col.pt` |
A string used to indicate the color of the plotted points. Will be transparent unless |

`transparency` |
A numeric that indicates how many points would be plotted on top of each other before the ‘point’ would have the full |

`plot.p` |
A logical that indicates if the proportion for categorized values of X are plotted ( |

`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 |

`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 ( |

`data` |
The data frame from which the formula should be evaluated. |

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.

None. However, a plot is produced.

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.

Derek H. Ogle, derek@derekogle.com

## 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(temperature,fail,fail2=factor(fail,levels=c("yes","no"))) ## Default plot (using formula notation) plotBinResp(fail~temperature,data=d) plotBinResp(fail2~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))

[Package *FSA* version 0.8.26.9000 Index]