logRegr

Userfriendly wrapper to do logistic regression in R

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

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

The formula, specified in the same way as for 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 findShortestInterval.

theme

The theme used to display the plot.

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.

See Also

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

Aliases
  • logRegr
Examples
# NOT RUN {
### 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);
# }
Documentation reproduced from package userfriendlyscience, version 0.7.2, License: GPL (>= 3)

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