screeplot_mda

The scree plot shows each factor along the X axis, and the proportion of
common variance explained by that factor on the Y axis. The proportion of
common variance explained is given by the factor eigenvalue.

Multi-Dimensional Analysis (MDA) is an adaptation of factor
analysis developed by Douglas Biber (1992) <doi:10.1007/BF00136979>. Its most
common use is to describe language as it varies by genre, register, and use.
This package contains functions for carrying out the calculations needed to
describe and plot MDA results: dimension scores, dimension means, and factor
loadings.

David Brown

mda.biber

Functions for Multi-Dimensional Analysis

Alex Reinhart

screeplot_mda function

<dl><dt>obs_by_group</dt>
<dd>A data frame containing 1 categorical (factor) variable
and continuous (numeric) variables.</dd>
<dt>cor_min</dt>
<dd>The correlation threshold for including variables in the
factor analysis.</dd></dl>

Arguments

Scree plot for multi-dimensional analysis — screeplot_mda

<dl>

<dt>obs_by_group</dt>
<dd>A data frame containing 1 categorical (factor) variable
and continuous (numeric) variables.</dd>


<dt>cor_min</dt>
<dd>The correlation threshold for including variables in the
factor analysis.</dd>

</dl>

screeplot_mda: Scree plot for multi-dimensional analysis

Description

Usage

Value

Arguments

Details

See Also