block.random

Random assignment of n subjects with an equal number in all of N conditions may done by block randomization, where the block size is the number of experimental conditions. The number of Independent Variables and the number of levels in each IV are specified as input. The output is a the block randomized design.

multivariate

A general purpose toolbox developed originally for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Validation and cross validation of scales developed using basic machine learning algorithms are provided, as are functions for simulating and testing particular item and test structures. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, including mediation models, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r/> web page.

William Revelle

psych

Procedures for Psychological, Psychometric, and Personality
Research

block.random function

<dl> <dt>n</dt>
<dd>The number of subjects to randomize. Must be a multiple of the number of experimental conditions</dd><dt>ncond</dt>
<dd>The number of conditions for each IV. Defaults to 2 levels for one IV. If more than one IV, specify as a vector. If names are provided, they are used, otherwise the IVs are labeled as IV1 ... IVn</dd></dl>

Arguments

Author

Create a block randomized structure for n independent variables — block.random

<dl>

 <dt>n</dt>
<dd>The number of subjects to randomize. Must be a multiple of the number of experimental conditions</dd>

<dt>ncond</dt>
<dd>The number of conditions for each IV. Defaults to 2 levels for one IV. If more than one IV, specify as a vector. If names are provided, they are used, otherwise the IVs are labeled as IV1 ... IVn</dd>

</dl>

block.random: Create a block randomized structure for n independent variables

Description

Usage

Value

Arguments

Author

Examples