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MULTIVARIATE STATISTICAL MODELING WITH LATENT VARIABLES IN SOCIAL SCIENCES

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Venue: Birkbeck Main Building, MAL 458 (ITS)

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INTRODUCTION

The Multivariate Statistical Modeling with Latent Variables workshop (MSMLV) provides a thorough introduction to key techniques surrounding structural equation modeling (SEM).

Throughout the workshop, statistical knowledge is applied to real data and current examples. The seminars support attendees in embedding learning in a practical and applied manner.

The workshop spans 12 hours of lectures and laboratory sessions, focusing on the development of advanced statistical skills to help social science researchers on their quantitative research projects. The sessions will cover from the preparation of a research instrument to its estimation, interpretation, and reporting the outputs following the latest peer-reviewed journal standards.

Multivariate data analysis with latent variables is considered to be advanced, and although no previous knowledge of statistics is required to attend this module.

 

THE AIMS OF THIS WORKSHOP

The overall aim of the MSMLV workshop is to provide social science researchers with a fundamental understanding of the basic tools and concepts of multivariate data analysis with latent variables. In addition, it will provide a foundation to assess analyses required in rigorous peer-reviewed venues.

 

More specifically, the workshop aims to:

-       introduce attendees to core multivariate data analysis functions,

-       facilitate the development of an understanding of the key concepts and applications encountered in quantitative research,

-       provide attendees with the knowledge and skills required to collect data and apply multivariate analysis techniques effectively,

-       provide attendees with the knowledge and skills required to develop and test their own theoretical frameworks,

-       support attendees with the knowledge necessary to report multivariate data analysis following peer-reviewed journal standards.

 

THE LEARNING OUTCOMES FOR THIS WORKSHOP
Learning outcomes describe what attendees should know and be able to do by the end of the workshop. 

Knowledge and understanding

After attending this workshop attendees should be able to:

-       demonstrate an understanding of the advantages of SEM to test conceptual structures,

-       demonstrate an understanding of the different types of conceptual models’ analysis,

-       understand how to calculate, interpret, and report the results obtained,

-       demonstrate an appreciation of the fundamental techniques and concepts within SEM, including Confirmatory Factor Analysis (CFA), latent variable path analysis, and mediation and moderation analyses.

 

Skills, qualities, and attributes

After attending this workshop attendees should be able to:

-       provide empirical field research aimed to test theoretical relationship between variables,

-       make use of appropriate tests when examining quantitative data,

-       apply SEM principles to a range of methodological issues,

-       professionally report the outputs of multivariate statistical modeling with latent variables.

 

WORKSHOP SPECIFICATION

Computers should be available at the hosting institution. However, attendees are welcome to bring their own personal computer (laptop).

The following packages should be installed and running:

                          -  IBM SPSS® Statistics

                          -  IBM Amos®

                          -  PROCESS Macro for IBM SPSS Statistics®. Free macro available on the link: http://www.processmacro.org/download.html

                          -  Microsoft Office®

The Multivariate Statistical Modeling with Latent Variables workshop is best designed for groups of a maximum of 15 attendees.

  

INSTRUCTOR

Bruno Schivinski, Ph.D. is a sociologist and lecturer in marketing at Birkbeck, University of London. He consults for online service providers, websites, and scientific institutions such as the Polish Ministry of Science and Higher Education (MNiSW) and the National Science Centre (NCN). Dr. Schivinski specializes in quantitative research methods with focus on multivariate data analysis. His latest work can be found in the Journal of Advertising Research, Industrial Marketing Management, Journal of Strategic Marketing, and Event Management. 

Personal website: https://brunoschivinski.wordpress.com/

 

MODULE TIMETABLE 
The Multivariate Statistical Modeling with Latent Variables workshop follows two working days timetable (06 June 2019 – Thursday and 07 June 2019 Friday).

Each day accommodates two sessions:

Morning 10:00am – 1:00pm (3 hours)

Afternoon 2:00pm – 5:00pm (3hours)

Rendering a total of 12 hours including lectures and practical seminars.

 

ATTENDANTS
The MSMLV is limited to a number of 15 Ph.D. students. Preference is given to Ph.D. students, which research projects deal with survey analysis using latent variables. 

 

APPLY ONLINE: https://bbk.qualtrics.com/jfe/form/SV_5sYgpbnVJJOJqLz

 

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