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Implements the Quantile Composite-based Path Modeling approach
(Davino and Vinzi, 2016 <doi:10.1007/s11634-015-0231-9>;
Dolce et al., 2021 <doi:10.1007/s11634-021-00469-0>). The method complements the traditional PLS Path Modeling approach, analyzing the entire distribution of outcome variables and, therefore, overcoming the classical exploration of only average effects. It exploits quantile regression to investigate changes in the relationships among constructs and between constructs and observed variables.

Giuseppe Lamberti

qcpm

Quantile Composite Path Modeling

Cristina Davino

Pasquale Dolce

Domenico Vistocco

qc function

<dl><dt>x</dt>
<dd>the covariate variables</dd>
<dt>y</dt>
<dd>the dependent variable</dd>
<dt>tau</dt>
<dd>the quantile(s) to be estimated</dd></dl>

Arguments

qc — qc

<dl>

<dt>x</dt>
<dd>the covariate variables</dd>


<dt>y</dt>
<dd>the dependent variable</dd>


<dt>tau</dt>
<dd>the quantile(s) to be estimated</dd>

</dl>

qc: qc

Description

Usage

Value

Arguments

Details