CODICE CORSO: I-WS21 LINGUA: RESIDENZIALE

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 covariancebased 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 PLSSEM 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 2017 edition of this course has unfortunately already taken place and no further dates are scheduled for the current calender year.

Should you be interested in receiving notification regarding course dates for 2018, please contact us at training@tstat.eu.

Students*: € 598.00

Academic: € 996.00

Government /Nonprofi t: € 1106.00

Commercial: € 1215.00

 

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

 

All fees are subject to VAT (applied at the current Italian rate of 22%).

 

Please note that a non-refundable deposit of €100.00 for students and €200.00 for academic, Government/Nonprofit 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: i) teaching materials (copies of lecture slides, databases and Stata routines used during the workshop); ii) a temporary licence of Stata valid for 30 days from the beginning of the workshop; iii) half board accommodation (breakfast, lunch and coffee breaks) in a single room at the Centro Studi CISL from Sunday 7th to Tuesday 9th May 2017 (2 nights).

 

In order to maximize the usefulness of this workshop, we recommend that participants bring their own laptops with them, in order to be able to actively participate in the empirical sessions.

 

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 22nd of April 2017.


L’iscrizione al corso dovrà avvenire tramite lo specifico modulo di registrazione e pervenire a TStat S.r.l. almeno 15 giorni prima dell’inizio del corso stesso. E’ possibile richiedere il modulo di registrazione compilando il seguente form oppure inviando una mail a formazione@tstat.it


NOME*


EMAIL*


OGGETTO


IL TUO MESSAGGIO


Termini e condizioni*
Autorizzo il trattamento dei dati personali ai sensi dell'articolo 13 del D.lgs. n.196/2003 - Testo completo



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 covariancebased 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 PLSSEM 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.