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rockchalk (version 1.8.0)

Regression Estimation and Presentation

Description

A collection of functions for ease of presentation and interpretation of regression analysis. These functions are developed in response to student requests that have arisen in our regression course. For regression diagnostics, see mcDiagnose, getDeltaRsquare, meanCenter or residualCenter. See the outreg function for a way to generate LaTeX tables of regression models. For nice, easy to use pictures, see plotSlopes, plotCurves, plotPlane for graphs. There are some functions for re-organization of data, especially useful might be combineLevels for re-coding factors. The vignette "rockchalk" offers a fairly broad survey. The package title "rockchalk" refers to the expression, "Rock Chalk Jayhawk, Go K.U.".

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Version

Install

install.packages('rockchalk')

Monthly Downloads

13,676

Version

1.8.0

License

GPL (>= 3.0)

Maintainer

Paul Johnson

Last Published

July 30th, 2013

Functions in rockchalk (1.8.0)

Multi-collinearity diagnostics

Cheating and Looting in Japanese Electoral Politics

recode a factor by "combining" levels

Create covariance matrix from correlation and standard deviation information

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

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

Generic function for plotting regressions and interaction effects

rockchalk-package

Miscellaneous regression functions

predictOMatic creates predicted values for a fitted regression model. This demonstrates marginal effects of the predictor variables.

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

makeVec for checking or creating vectors

Check a matrix for positive definitness

Converts the R-square to the variance inflation factor

genCorrelatedData2

Generates a data frame for regression analysis.

getFocal.factor

Select focal values from factor variables.

Creates a publication quality result table for regression models. outreg0 is the last version in the last development stream.

Religious beliefs and crime rates

Estimate standardized regression coefficients for all variables

genCorrelatedData

Generates a data frame for regression analysis

Create correlation matrices.

Estimate leave-one-variable-out regressions

Minor revision of mvrnorm (from MASS) to facilitate replication

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

Creates a publication quality result table for regression models.

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

print.factorSummaries

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

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

summarizeFactors

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

summarizeNumerics

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

getFocal.default

Select focal values from a numeric variable

getDeltaRsquare

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

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

Hypothesis tests for Simple Slopes Objects

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

mcGraph2 draws a 3-D representation of a scatterplot with shadows in the x1-x2 plane.

mcGraph3 draws a 3-dimensional scatter and a regression plane

Calculates a "residual-centered" interaction regression.

Tabulates observed values and calculates entropy

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

Create a focal value vector.

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

magRange Magnify the range of a variable.

Central Tendency estimates for variables

Convert an outreg result to HTML markup

Assists creation of predicted value curves for regression models.

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

Illustrate the effect of multicollinearity in regression.

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

Select most frequently occurring values from numeric or categorical variables.

Select focal values from an observed variable.

Superimpose regression lines on a plotted plane

Creates the newdata frame required in predict methods.

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

Create sequences for plotting