logRegr: Userfriendly wrapper to do logistic regression in R

In psytext/rosetta: Parallel Use of Statistical Packages in Teaching

Description

This function is meant as a userfriendly wrapper to approximate the way logistic regression is done in SPSS.

Usage

logRegr(formula, data = NULL, conf.level = 0.95, digits = 2,
  pvalueDigits = 3, crossTabs = TRUE, plot = FALSE,
  collinearity = FALSE, env = parent.frame(),
  predictionColor = viridis::viridis(3)[3], predictionAlpha = 0.5,
  predictionSize = 2, dataColor = viridis::viridis(3)[1],
  dataAlpha = 0.33, dataSize = 2,
  observedMeansColor = viridis::viridis(3)[2], binObservedMeans = 7,
  observedMeansSize = 2, observedMeansWidth = NULL,
  observedMeansAlpha = 0.5, theme = ggplot2::theme_bw())

## S3 method for class 'logRegr'
print(x, digits = x$input$digits,
  pvalueDigits = x$input$pvalueDigits, ...)

Arguments

formula	The formula, specified in the same way as for stats::glm() (which is used for the actual analysis).
data	Optionally, a dataset containing the variables in the formula (if not specified, the variables must exist in the environment specified in env.
conf.level	The confidence level for the confidence intervals.
digits	The number of digits used when printing the results.
pvalueDigits	The number of digits used when printing the p-values.
crossTabs	Whether to show cross tabulations of the correct predictions for the null model and the tested model, as well as the percentage of correct predictions.
plot	Whether to display the plot.
collinearity	Whether to show collinearity diagnostics.
env	If no dataframe is specified in data, use this argument to specify the environment holding the variables in the formula.
predictionColor, dataColor, observedMeansColor	The color of, respectively, the line and confidence interval showing the prediction; the points representing the observed data points; and the means based on the observed data.
predictionAlpha, dataAlpha, observedMeansAlpha	The alpha of, respectively, the confidence interval of the prediction; the points representing the observed data points; and the means based on the observed data (set to 0 to hide an element).
predictionSize, dataSize, observedMeansSize	The size of, respectively, the line of the prediction; the points representing the observed data points; and the means based on the observed data (set to 0 to hide an element).
binObservedMeans	Whether to bin the observed means; either FALSE or a single numeric value specifying the number of bins.
observedMeansWidth	The width of the lines of the observed means. If not specified (i.e. NULL), this is computed automatically and set to the length of the shortest interval between two successive points in the predictor data series (found using ufs::findShortestInterval().
theme	The theme used to display the plot.
x	logRegr object
...	other print parameters

Details

This function

Value

Mainly, this function prints its results, but it also returns them in an object containing three lists:

input	The arguments specified when calling the function
intermediate	Intermediat objects and values
output	The results, such as the plot, the cross tables, and the coefficients.

Author(s)

Ron Pat-El & Gjalt-Jorn Peters (both while at the Open University of the Netherlands)

Maintainer: Gjalt-Jorn Peters [e-mail]

See Also

regr and fanova for similar functions for linear regression and analysis of variance and stats::glm() for the regular interface for logistic regression.

Examples

### Simplest way to call logRegr
logRegr(data=mtcars, formula = vs ~ mpg);

### Also ordering a plot
logRegr(data=mtcars, formula = vs ~ mpg, plot=TRUE);

### Only use five bins
logRegr(data=mtcars, formula = vs ~ mpg, plot=TRUE, binObservedMeans=5);

psytext/rosetta documentation built on Dec. 5, 2019, 10:16 a.m.