Description Usage Arguments Details Value Examples

View source: R/prob-var-plot.R

`prob_var_plot`

creates a ggplot2 plot with a Bernoulli LOESS for
binary versus continuous variable. This should be useful as a way to
determine the relationship between a continuous variable and a binary
variable.

1 | ```
prob_var_plot(data, x_var, y_var, window_width, method = "bayes")
``` |

`data` |
The dataframe containing the binary and continuous variable |

`x_var` |
The name of the continuous variable (as a string) |

`y_var` |
The name of the binary response variable (as a string) |

`window_width` |
Width of the window to use for approximating p. |

`method` |
The method to be used to find confidence intervals for binomial variables. See documentation for binom.confint for options. |

It returns a ggplot2 plot, so one could easily add other elements to the plot, such as titles, axes labels, and other themes.

A ggplot2 plot.

1 2 3 4 5 6 | ```
x <- rnorm(100, 0, 2)
y <- rbinom(100, 1, invlogit(x))
test_data <- data.frame(x, y)
p <- prob_var_plot(test_data, "x", "y", 2)
p
p + labs(title="Empirical probability versus Gaussian variable")
``` |

wjones127/thesis documentation built on May 28, 2017, 4:36 a.m.

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