regr
regr: a simple regression analysis wrapper
The regr
function wraps a number of linear regression functions into
one convenient interface that provides similar output to the regression
function in SPSS. It automatically provides confidence intervals and
standardized coefficients. Note that this function is meant for teaching
purposes, and therefore it's only for very basic regression analyses.
 Keywords
 utilities
Usage
regr(formula, dat = NULL, conf.level = .95, digits = 2, pvalueDigits = 3, coefficients = c("raw", "scaled"), plot = FALSE, ci.method = c("widest", "r.con", "olkinfinn"), ci.method.note = FALSE, env = parent.frame())
Arguments
 formula

The formula of the regression analysis, of the form
y ~ x1 + x2
, where y is the dependent variable and x1 and x2 are the predictors.  dat
 If the terms in the formula aren't vectors but variable names, this should be the dataframe where those variables are stored.
 conf.level
 The confidence of the confidence interval around the regression coefficients.
 digits
 Number of digits to round the output to.
 pvalueDigits
 The number of digits to show for pvalues; smaller pvalues will be shown as
 coefficients
 Which coefficients to show; can be "raw" to only show the raw (unstandardized) coefficients; "scaled" to only show the scaled (standardized) coefficients), or c("raw", "scaled') to show both.
 plot
 For regression analyses with only one predictor (also sometimes confusingly referred to as 'univariate' regression analyses), scatterplots with regression lines and their standard errors can be produced.
 ci.method, ci.method.note
 Which method to use for the confidence interval around R squared, and whether to display a note about this choice.
 env
 The enviroment where to evaluate the formula.
Value

A list of three elements:
A list of three elements:
Examples
### Do a simple regression analysis
regr(age ~ circumference, dat=Orange);
### Show more digits for the pvalue
regr(Orange$age ~ Orange$circumference, pvalueDigits=18);
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