Regression Estimation and Presentation
Superimpose regression lines on a plotted plane
Find numeric columns, center them, re-name them, and join them with th...
Central Tendency estimates for variables
A way of checking if a string is a valid file name.
Check a matrix for positive definitness
recode a factor by "combining" levels
Calculates the "center" quantiles, always including the median, when n...
Returns center values of x, the mean, mean-std.dev, mean+std.dev
Select most frequently occurring values from numeric or categorical va...
Create an ordinal variable by grouping numeric data input.
Summary stats table-maker for regression users
Create a uniquely named directory. Appends number & optionally date to...
draw a normal distribution with beautiful illustrations
Create a focal value vector.
Prints out the contents of an object created by summarizeFactors in th...
Reformat numeric summarize output as one column per variable, similar ...
Generates a data frame for regression analysis
Generates a data frame for regression analysis.
Generate correlated data for simulations (third edition)
Generate correlated data (predictors) for one unit
retrieves estimates of the coefficient of determination from a list of...
Calculates the delta R-squares, also known as squared semi-partial cor...
Select focal values from an observed variable.
Calculates partial correlation coefficients after retrieving data matr...
Converts the R-square to the variance inflation factor
Group Mean Center: Generate group summaries and individual deviations ...
Calculate excess kurtosis
Create correlation matrices.
Create covariance matrix from correlation and standard deviation infor...
Estimate leave-one-variable-out regressions
magRange Magnify the range of a variable.
Create Symmetric Matrices, possibly covariance or correlation matrices...
makeVec for checking or creating vectors
Multi-collinearity diagnostics
Illustrate multicollinearity in regression, part 1.
meanCenter
Create a data frame suitable for estimating a model
Create a "raw" (UNTRANSFORMED) data frame equivalent to the input data...
Minor revision of mvrnorm (from MASS
) to facilitate replication
Create a newdata frame for usage in predict methods
Creates a publication quality result table for regression models. Work...
Convert LaTeX output from outreg to HTML markup
Pad with 0's.
Creates a cross tabulation with counts and percentages
perspEmpty
Plot testSlopes objects
Assists creation of predicted value curves for regression models.
Regression plots with predicted value lines, confidence intervals, col...
Draw display for discrete predictor in plotSlopes
Draw a 3-D regression plot for two predictors from any linear or nonli...
Create sequences for plotting
Generic function for plotting regressions and interaction effects
Calculate a predicted value matrix (fit, lwr, upr) for a regression, e...
Create predicted values after choosing values of predictors. Can demon...
Display pctable objects
print method for output from summarize
print method for summary.pctable objects
Stack together data frames
Remove NULL values variables from a list
Calculates a "residual-centered" interaction regression.
rockchalk: regression functions
Draw standard error bar for discrete variables
Calculate skewness
Estimate standardized regression coefficients for all variables
Sorts numeric from discrete variables and returns separate summaries f...
Extracts non-numeric variables, calculates summary information, includ...
Extracts numeric variables and presents an summary in a workable forma...
Tabulates observed values and calculates entropy
Extract presentation from a pctable object
Hypothesis tests for Simple Slopes Objects
Convert the vech (column of strictly lower trianglar values from a mat...
Convert a half-vector (vech) into a matrix.
T-test for the difference in 2 regression parameters
A collection of functions for interpretation and presentation of regression analysis. These functions are used to produce the statistics lectures in <https://pj.freefaculty.org/guides/>. Includes regression diagnostics, regression tables, and plots of interactions and "moderator" variables. The emphasis is on "mean-centered" and "residual-centered" predictors. The vignette 'rockchalk' offers a fairly comprehensive overview. The vignette 'Rstyle' has advice about coding in R. The package title 'rockchalk' refers to our school motto, 'Rock Chalk Jayhawk, Go K.U.'.