mean_replacement

The <code>seminr</code> package provides a natural syntax for researchers to describe PLS
structural equation models.

A powerful, easy to syntax for specifying and estimating complex
Structural Equation Models. Models can be estimated using Partial
Least Squares Path Modeling or Covariance-Based Structural Equation
Modeling or covariance based Confirmatory Factor Analysis. Methods described in Ray, Danks, and Valdez (2021).

Nicholas Danks

seminr

Building and Estimating Structural Equation Models

Soumya Ray

Nicholas Patrick Danks

André Calero Valdez

Juan Manuel Velasquez Estrada

James Uanhoro

Johannes Nakayama

Lilian Koyan

Laura Burbach

Arturo Heynar Cano Bejar

Susanne Adler

mean_replacement function

<dl><dt>data</dt>
<dd>A dataset to be used for estimating a SEMinR model</dd></dl>

Arguments

Function to clean data of omitted values by mean replacement — mean_replacement

<dl>

<dt>data</dt>
<dd>A dataset to be used for estimating a SEMinR model</dd>

</dl>

Function to clean data of omitted values by mean replacement

mean_replacement: Function to clean data of omitted values by mean replacement

Description

Usage

Value

Arguments

Details

References