COURSE ID: I-WS21 LANGUAGE:

INTRODUCTION TO PARTIAL LEAST SQUARES STRUCTURAL EQUATION MODELLING (PLSSEM) USING STATA

PLS-SEM, also referred to as partial least squares path modelling, is a type of SEM, which is being increasing used in social sciences, psychology, business administration and marketing. In a nutshell, PLS-SEM can be viewed as a component-based SEM alternative to the covariance-based structural equation modelling (CB-SEM) which can be described as a factor-based SEM technique. As such, the PLS-SEM approach provides researchers with a multivariate statistical technique that can readily be used to estimate exploratory or/and complex SEM models. Although there are several stand-alone specialized PLS-SEM software packages available, this course introduces participants to the PLS-SEM methodology, through the user-written Stata-package, plssem, developed by the course instructors themselves.

In common with TStat’s workshop philosophy, throughout the workshop, theoretical sessions are reinforced by case study examples, in which the course tutor discusses current research issues, highlighting potential pitfalls and the advantages of individual techniques. In this manner, course leaders are able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data.

At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed during the workshop.

The PLS-SEM workshop is of particular interest to researchers and professional working in social sciences, psychology, business administration, marketing and management. Due to its introductory nature however, is it also accessible to individuals, regardless of their respective disciplines or fields, who need to acquire the requisite toolset to apply the PLS-SEM methodology to their own data.

When possible, participants should bring their own datasets to the workshop to work with and discuss with the instructors.

It is assumed that participants have previously followed a basic course in statistics. Previous exposure to Stata or other statistical software packages would also be an advantage.

SESSION I: INTRODUCTION

What is structural equation modeling (SEM)?
Different approaches to SEM
What is PLS-SEM?
PLS-SEM versus CB-SEM

 

SESSION II: BASIC CONCEPTS

Regression
Principal component analysis
Path analysis
Bootstrapping
Reflective and formative measures

 

SESSION III: DEVELOPING AND ASSESSING A PLS-SEM MODEL

Developing the model

Specification
Example study and measures
Estimation using plssem package in Stata

Assessing the model

Measurement model
Construct and discriminant validity

Structural model

Goodness of fit
Path coefficients

 

SESSION IV: ADVANCED PLS-SEM MODELS USING PLSSEM PACKAGE IN STATA

Mediation analysis

Barron and Kenny approach and its alternatives
Mediation analysis with observed variables
Mediation analysis with latent variables

Multiple sample models

Multi-group approach
MIMIC approach

Higher-order factor models

Second-order factor models

Interaction-based models

Product-term approach

PLS-SEM models including categorical variables

 

SESSION V: HOW TO PUBLISH A PLS-SEM STUDY

Scientific journal criteria
Example studies

 

SESSION VI: HOW TO USE STORED INFO FROM PLSSEM PACKAGE

Accessing scalars, macros and matrices

The course will be held in Milan, on the 28th and 29th of June 2018.

Students*: € 540.00
Academic: € 900.00
Non-Profit/Public Research Centres: € 1050.00
Commercial: € 1200.00

*To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year.

Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number.

Please note that a non-refundable deposit of €100.00 for students and €200.00 for Academic, Non-Profit/Public Research Centres and Commercial participants, is required to secure a place and is payable upon registration. The number of participants is limited to 15. Places will be allocated on a first come, first serve basis.

Course fees cover: teaching materials (handouts, Stata do files and datasets to used during the course), a temporary licence of Stata valid for 30 days from the beginning of the workshop, light lunch and coffee breaks.

To maximize the usefulness of this workshop, we strongly recommend that participants bring their own laptops with them, to enable them to actively participate in the empirical sessions.

 

REGISTRATION DEADLINE

Individuals interested in attending this workshop must return their completed registration forms either by email (training@tstat.eu) or by fax (+39 0864 206014) to TStat by the 8th of June 2018.


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PLS-SEM, also referred to as partial least squares path modelling, is a type of SEM, which is being increasing used in social sciences, psychology, business administration and marketing. In a nutshell, PLS-SEM can be viewed as a component-based SEM alternative to the covariance-based structural equation modelling (CB-SEM) which can be described as a factor-based SEM technique. As such, the PLS-SEM approach provides researchers with a multivariate statistical technique that can readily be used to estimate exploratory or/and complex SEM models. Although there are several stand-alone specialized PLS-SEM software packages available, this course introduces participants to the PLS-SEM methodology, through the user-written Stata-package, plssem, developed by the course instructors themselves.