logRegr | R Documentation |
This function is meant as a userfriendly wrapper to approximate the way logistic regression is done in SPSS.
logRegr( formula, data = NULL, conf.level = 0.95, digits = 2, predictGroupValue = NULL, comparisonGroupValue = NULL, pvalueDigits = 3, crossTabs = TRUE, oddsRatios = TRUE, plot = FALSE, collinearity = FALSE, env = parent.frame(), predictionColor = rosetta::opts$get("viridis3")[3], predictionAlpha = 0.5, predictionSize = 2, dataColor = rosetta::opts$get("viridis3")[1], dataAlpha = 0.33, dataSize = 2, observedMeansColor = rosetta::opts$get("viridis3")[2], binObservedMeans = 7, observedMeansSize = 2, observedMeansWidth = NULL, observedMeansAlpha = 0.5, theme = ggplot2::theme_bw(), headingLevel = 3 ) rosettaLogRegr_partial( x, digits = x$input$digits, pvalueDigits = x$input$pvalueDigits, headingLevel = x$input$headingLevel, echoPartial = FALSE, partialFile = NULL, quiet = TRUE, ... ) ## S3 method for class 'rosettaLogRegr' knit_print( x, digits = x$input$digits, headingLevel = x$input$headingLevel, pvalueDigits = x$input$pvalueDigits, echoPartial = FALSE, partialFile = NULL, quiet = TRUE, ... ) ## S3 method for class 'rosettaLogRegr' print( x, digits = x$input$digits, pvalueDigits = x$input$pvalueDigits, headingLevel = x$input$headingLevel, forceKnitrOutput = FALSE, ... )
formula |
The formula, specified in the same way as for
|
data |
Optionally, a dataset containing the variables in the formula
(if not specified, the variables must exist in the environment specified in
|
conf.level |
The confidence level for the confidence intervals. |
digits |
The number of digits used when printing the results. |
predictGroupValue, comparisonGroupValue |
Can optionally be used to set the value to predict and the value to compare with. |
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. |
oddsRatios |
Whether to also present the regression coefficients
as odds ratios (i.e. simply after a call to |
plot |
Whether to display the plot. |
collinearity |
Whether to show collinearity diagnostics. |
env |
If no dataframe is specified in |
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. |
theme |
The theme used to display the plot. |
headingLevel |
The number of hashes to print in front of the headings |
x |
The object to print (i.e. as produced by |
echoPartial |
Whether to show the executed code in the R Markdown
partial ( |
partialFile |
This can be used to specify a custom partial file. The
file will have object |
quiet |
Passed on to |
... |
Any additional arguments are passed to the default print method
by the print method, and to |
forceKnitrOutput |
Force knitr output. |
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. |
Ron Pat-El & Gjalt-Jorn Peters (both while at the Open University of the Netherlands)
Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com
regr
and fanova
for similar functions
for linear regression and analysis of variance and stats::glm()
for the
regular interface for logistic regression.
### Simplest way to call logRegr rosetta::logRegr(data=mtcars, formula = vs ~ mpg); ### Also ordering a plot rosetta::logRegr( data=mtcars, formula = vs ~ mpg, plot=TRUE ); ### Only use five bins rosetta::logRegr( data=mtcars, formula = vs ~ mpg, plot=TRUE, binObservedMeans=5 ); ## Not run: ### Mimic output that would be obtained ### when calling from an R Markdown file rosetta::rosettaLogRegr_partial( rosetta::logRegr( data=mtcars, formula = vs ~ mpg, plot=TRUE ) ); ## End(Not run)
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