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rockchalk (version 1.8.157)

Regression Estimation and Presentation

Description

A collection of functions for interpretation and presentation of regression analysis. These functions are used to produce the statistics lectures in . 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.'.

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Version

Install

install.packages('rockchalk')

Monthly Downloads

13,238

Version

1.8.157

License

GPL (>= 3.0)

Maintainer

Paul Johnson

Last Published

August 6th, 2022

Functions in rockchalk (1.8.157)

Cheating and Looting in Japanese Electoral Politics

recode a factor by "combining" levels

Select most frequently occurring values from numeric or categorical variables.

Superimpose regression lines on a plotted plane

A way of checking if a string is a valid file name.

Central Tendency estimates for variables

Returns center values of x, the mean, mean-std.dev, mean+std.dev

Calculates the "center" quantiles, always including the median, when n is odd.

Find numeric columns, center them, re-name them, and join them with the original data.

Check a matrix for positive definitness

Create a focal value vector.

descriptiveTable

Summary stats table-maker for regression users

Create an ordinal variable by grouping numeric data input.

formatSummarizedNumerics

Reformat numeric summarize output as one column per variable, similar to R summary

Group Mean Center: Generate group summaries and individual deviations within groups

genCorrelatedData

Generates a data frame for regression analysis

Calculate excess kurtosis

Converts the R-square to the variance inflation factor

formatSummarizedFactors

Prints out the contents of an object created by summarizeFactors in the style of base::summary

Calculates partial correlation coefficients after retrieving data matrix froma fitted regression model

draw a normal distribution with beautiful illustrations

getDeltaRsquare

Calculates the delta R-squares, also known as squared semi-partial correlation coefficients.

dir.create.unique

Create a uniquely named directory. Appends number & optionally date to directory name.

Create correlation matrices.

Illustrate multicollinearity in regression, part 1.

Multi-collinearity diagnostics

genCorrelatedData2

Generates a data frame for regression analysis.

Create Symmetric Matrices, possibly covariance or correlation matrices, or check a matrix for symmetry and serviceability.

Create covariance matrix from correlation and standard deviation information

Regression plots with predicted value lines, confidence intervals, color coded interactions

plotFancyCategories

Draw display for discrete predictor in plotSlopes

Create a "raw" (UNTRANSFORMED) data frame equivalent to the input data that would be required to fit the given model.

model.data.default

Create a data frame suitable for estimating a model

Generate correlated data (predictors) for one unit

Creates a cross tabulation with counts and percentages

Minor revision of mvrnorm (from MASS) to facilitate replication

retrieves estimates of the coefficient of determination from a list of regressions

genCorrelatedData3

Generate correlated data for simulations (third edition)

plot.testSlopes

Plot testSlopes objects

print.summarize

print method for output from summarize

Assists creation of predicted value curves for regression models.

magRange Magnify the range of a variable.

Select focal values from an observed variable.

Creates a publication quality result table for regression models. Works with models fitted with lm, glm, as well as lme4.

Estimate leave-one-variable-out regressions

Create a newdata frame for usage in predict methods

print.summary.pctable

print method for summary.pctable objects

rockchalk-package

rockchalk: regression functions

Create sequences for plotting

Draw a 3-D regression plot for two predictors from any linear or nonlinear lm or glm object

Generic function for plotting regressions and interaction effects

Calculate a predicted value matrix (fit, lwr, upr) for a regression, either lm or glm, on either link or response scale.

Convert LaTeX output from outreg to HTML markup

Create predicted values after choosing values of predictors. Can demonstrate marginal effects of the predictor variables.

makeVec for checking or creating vectors

Sorts numeric from discrete variables and returns separate summaries for those types of variables.

summarizeFactors

Extracts non-numeric variables, calculates summary information, including entropy as a diversity indicator.

Tabulates observed values and calculates entropy

summarizeNumerics

Extracts numeric variables and presents an summary in a workable format.

Convert the vech (column of strictly lower trianglar values from a matrix) into a correlation matrix.

Convert a half-vector (vech) into a matrix.

summary.pctable

Extract presentation from a pctable object

Calculate skewness

Display pctable objects

Estimate standardized regression coefficients for all variables

Hypothesis tests for Simple Slopes Objects

Stack together data frames

Remove NULL values variables from a list

Religious beliefs and crime rates

Draw standard error bar for discrete variables

Calculates a "residual-centered" interaction regression.

T-test for the difference in 2 regression parameters