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>: Nitrogen
</li>
<li><code>W2</code>: Phosphorous
</li>
<li><code>W3</code>: Salt
</li>
</ul> Columns 4-7 correspond to the response categories for the question "What swine waste disposal methods do you use?"  Binary responses (1 = Yes, 0 = No) are provided for each category.
<ul>
<li><code>Y1</code>: Lagoon
</li>
<li><code>Y2</code>: Pit
</li>
<li><code>Y3</code>: Natural drainage
</li>
<li><code>Y4</code>: Holding tank
</li>
</ul> Columns 8-12 correspond to the response categories for the question "What are your primary sources of veterinary information?"  Binary responses (1 = Yes, 0 = No) are provided for each category.
<ul>
<li><code>Z1</code>: Professional consultant
</li>
<li><code>Z2</code>: Veterinarian
</li>
<li><code>Z3</code>: State or local extension service
</li>
<li><code>Z4</code>: Magazines
</li>
<li><code>Z5</code>: Feed companies and representatives
</li>
</ul> 

Format

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

Source