x100

Simulated data for demonstrating <code>blockTools</code> functionality.

datasets

Blocks units into experimental blocks, with one unit per treatment condition, by creating a measure of multivariate distance between all possible pairs of units. Maximum, minimum, or an allowable range of differences between units on one variable can be set. Randomly assign units to treatment conditions. Diagnose potential interference between units assigned to different treatment conditions. Write outputs to .tex and .csv files. For more information on the methods implemented, see Moore (2012) <doi:10.1093/pan/mps025>.

Ryan T Moore

blockTools

Block, Assign, and Diagnose Potential Interference in Randomized
Experiments

Keith Schnakenberg

x100 function

A dataframe with 100 rows and 6 columns.<dl>
 <dt>id</dt>
<dd>Identifies units.</dd> <dt>id2</dt>
<dd>Identifies subunits.</dd> <dt>b1</dt>
<dd>Numeric blocking variable 1.</dd> <dt>b2</dt>
<dd>Numeric blocking variable 2.</dd> <dt>g</dt>
<dd>Character variable to identify which of three groups each unit is 
 in (&#8220;a&#8221;, &#8220;b&#8221;, or &#8220;c&#8221;).</dd> <dt>ig</dt>
<dd>Numeric variable that can be ignored.</dd>
</dl>

Format

Author

Simulated data for demonstrating blockTools functionality — x100

A dataframe with 100 rows and 6 columns.<dl>
 <dt>id</dt>
<dd>Identifies units.</dd>

 <dt>id2</dt>
<dd>Identifies subunits.</dd>

 <dt>b1</dt>
<dd>Numeric blocking variable 1.</dd>

 <dt>b2</dt>
<dd>Numeric blocking variable 2.</dd>

 <dt>g</dt>
<dd>Character variable to identify which of three groups each unit is 
 in (&#8220;a&#8221;, &#8220;b&#8221;, or &#8220;c&#8221;).</dd>

 <dt>ig</dt>
<dd>Numeric variable that can be ignored.</dd>


</dl>

x100: Simulated data for demonstrating blockTools functionality

Description

Usage

Arguments

Format

Author

Examples