ena.rotate.by.hena.regression_2

This function allows user to provide a regression formula for rotation on x and optionally on y.
 If regression formula for y is not provide, svd is applied to the residual data deflated by x to get y coordinates.
 The regression formula should use ENA points as major predictors and a binary or numerical variable as dependent variable.
 Control and interaction variables are allowed to be included as predictors in the formula.

ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is a method used to identify meaningful and quantifiable patterns in discourse or reasoning. ENA moves beyond the traditional frequency-based assessments by examining the structure of the co-occurrence, or connections in coded data. Moreover, compared to other methodological approaches, ENA has the novelty of (1) modeling whole networks of connections and (2) affording both quantitative and qualitative comparisons between different network models.   Shaffer, D.W., Collier, W., & Ruis, A.R. (2016).

Cody L Marquart

rENA

Epistemic Network Analysis

Zachari Swiecki

Wesley Collier

Brendan Eagan

Roman Woodward

David Williamson Shaffer

ena.rotate.by.hena.regression_2 function

<dl><dt>enaset</dt>
<dd>An <code>ENAset</code></dd>
<dt>params</dt>
<dd>list of parameters, may include:
x_var: Regression formula for x direction, such as "lm(formula= Condition ~ V + GameHalf + Condition : GameHalf)",
where V always stands for the ENA points.
y_var: Regression formula, similar to x_var for y direction (optional).</dd></dl>

Arguments

ENA Rotate by regression (second way) — ena.rotate.by.hena.regression_2

<dl>

<dt>enaset</dt>
<dd>An <code>ENAset</code></dd>


<dt>params</dt>
<dd>list of parameters, may include:
x_var: Regression formula for x direction, such as "lm(formula= Condition ~ V + GameHalf + Condition : GameHalf)",
where V always stands for the ENA points.
y_var: Regression formula, similar to x_var for y direction (optional).</dd>

</dl>

ena.rotate.by.hena.regression_2: ENA Rotate by regression (second way)

Description

Usage

Value

Arguments