farmer3

Responses for three MRCVs from a survey of Kansas farmers.  This data was first examined by Bilder and Loughin (2007).

The MRCV package provides functions for analyzing the association between
    one single response categorical variable (SRCV) and one multiple response
    categorical variable (MRCV), or between two or three MRCVs.  A modified Pearson
    chi-square statistic can be used to test for marginal independence for the one or
    two MRCV case, or a more general loglinear modeling approach can be used to examine
    various other structures of association for the two or three MRCV case.  Bootstrap-
    and asymptotic-based standardized residuals and model-predicted odds ratios are
    available, in addition to other descriptive information.

Natalie Koziol

MRCV

Methods for Analyzing Multiple Response Categorical Variables
        (MRCVs)

farmer3 function

The data frame contains the following 12 columns:

Columns 1-3 correspond to the response categories for the question "Which of the following do you test your swine waste for?"  Binary responses (1 = Yes, 0 = No) are provided for each category.
<ul><li><code>W1</code>:</li></ul> {Nitrogen}
<item><code>W2</code>:</item> {Phosphorous}
<item><code>W3</code>:</item> {Salt}

format

itemize

item

Bilder, C. and Loughin, T. (2007)  Modeling association between two or more categorical variables that allow for multiple category choices.  <em>Communications in Statistics--Theory and Methods</em>, <b>36</b>, 433--451.

farmer3: Data for Three MRCVs from the Kansas Farmer Survey

Description

Usage

Arguments

format

itemize

item

source