# 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:

The arguments specified when calling the function

Intermediat objects and values

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.

##### 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)*