plank

Abebe et al. (2001) discuss a dataset resulting from a three-way
layout for a neurological experiment in which the time
 required for a mouse to exit a narrow elevated wooden plank is
 measured. The response is the log of time (in seconds) to exit.
Interest lies in assessing the effects of three factors:
the Mouse Strain
(Tg+, Tg-),
 the mouse's Gender (female, male), and the mouse's Age (Aged, Middle, Young).
The design is a 2 by 2 by 3 factorial design.

datasets

Accompanies the book "Nonparametric Statistical Methods Using R, 2nd Edition" by Kloke and McKean (2024, ISBN:9780367651350).  Includes methods, datasets, and random number generation useful for the study of robust and/or nonparametric statistics.  Emphasizes classical nonparametric methods for a variety of designs --- especially one-sample and two-sample problems.  Includes methods for general scores, including estimation and testing for the two-sample location problem as well as Hogg's adaptive method.

John Kloke

npsm

Nonparametric Statistical Methods

Joseph McKean

plank function

A data frame with 64 observations on the following 4 variables.<dl>
 <dt><code>response</code></dt>
<dd>a numeric vector</dd> <dt><code>strain</code></dt>
<dd>a factor with levels <code>1</code> <code>2</code></dd> <dt><code>gender</code></dt>
<dd>a factor with levels <code>1</code> <code>2</code></dd> <dt><code>age</code></dt>
<dd>a factor with levels <code>1</code> <code>2</code> <code>3</code></dd> 
</dl>

Format

Plank data — plank

A data frame with 64 observations on the following 4 variables.<dl>
 <dt><code>response</code></dt>
<dd>a numeric vector</dd>

 <dt><code>strain</code></dt>
<dd>a factor with levels <code>1</code> <code>2</code></dd>

 <dt><code>gender</code></dt>
<dd>a factor with levels <code>1</code> <code>2</code></dd>

 <dt><code>age</code></dt>
<dd>a factor with levels <code>1</code> <code>2</code> <code>3</code></dd>

 
</dl>

plank: Plank data

Description

Usage

Arguments

Format

References

Examples