Learn R Programming
⚠️There's a newer version (0.3-3) of this package.Take me there.

MRCV (version 0.1-0)

Methods for Analyzing Multiple Response Categorical Variables (MRCVs)

Description

This package provides functions for analyzing the association between two or three MRCVs. A modified Pearson chi-square statistic can be used to test for marginal independence, or a more general loglinear modeling approach can be used to compare various other structures of association. Bootstrap- and asymptotic-based standardized residuals and model-predicted odds ratios are available, in addition to other descriptive information.

Copy Link

Version

Install

install.packages('MRCV')

Monthly Downloads

469

Version

0.1-0

License

GPL (>= 3)

Maintainer

Natalie Koziol

Last Published

June 23rd, 2013

Functions in MRCV (0.1-0)

MRCV-package

Statistical Methods for Analyzing the Association Among Two or Three MRCVs
print.SPMI

Control Printed Display of Objects of Class "SPMI"
item.response.table

Create an Item Response Table or Data Frame
summary.genloglin

Summarize Two or Three MRCV Model Fit Information
anova.genloglin

Perform MRCV Model Comparison Tests
MRCV-internal

Internal MRCV Package Functions
farmer2

Kansas Farmer Data of Bilder and Loughin (2007)
predict.genloglin

Calculate Observed and Model-Predicted Odds Ratios for MRCV Data
genloglin

Model the Association Among Two or Three MRCVs
marginal.table

Create a Marginal Table
print.genloglin

Control Printed Display of MRCV Regression Modeling Objects
SPMI.test

Test for Marginal Independence Between Two MRCVs
residuals.genloglin

Calculate Standardized Pearson Residuals for MRCV Data
farmer3

Kansas Farmer Data of Bilder and Loughin (2007)