orob2

&#8220;A 2 x 2 factorial experiment comparing 2 types of seed and 2 root extracts. There are 5 or 6 replicates in each 
 of the 4 treatment groups, and each replicate comprises a number of seeds varying between 4 and 81. The response 
 variable is the proportion of seeds germinating in each replicate.&#8221; (Crowder, 1978, Table 3).

datasets

Provides a set of functions to analyse
overdispersed counts or proportions. Most of the methods are
already available elsewhere but are scattered in different
packages. The proposed functions should be considered as
complements to more sophisticated methods such as generalized
estimating equations (GEE) or generalized linear mixed effect
models (GLMM).

Renaud Lancelot

Analysis of Overdispersed Data

orob2 function

A data frame with 21 observations on the following 4 variables.<dl>
 <dt>seed</dt>
<dd>a factor with 2 levels: <code>O73</code> and <code>O75</code>.</dd> <dt>root</dt>
<dd>a factor with 2 levels <code>BEAN</code> and <code>CUCUMBER</code>.</dd> <dt>n</dt>
<dd>a numeric vector: the number of seeds exposed to germination.</dd> <dt>y</dt>
<dd>a numeric vector: the number of seeds which actually germinated.</dd> 
</dl>

Format

Germination Data — orob2

A data frame with 21 observations on the following 4 variables.<dl>
 <dt>seed</dt>
<dd>a factor with 2 levels: <code>O73</code> and <code>O75</code>.</dd>

 <dt>root</dt>
<dd>a factor with 2 levels <code>BEAN</code> and <code>CUCUMBER</code>.</dd>

 <dt>n</dt>
<dd>a numeric vector: the number of seeds exposed to germination.</dd>

 <dt>y</dt>
<dd>a numeric vector: the number of seeds which actually germinated.</dd>

 
</dl>

orob2: Germination Data

Description

Usage

Arguments

Format

References