Monday, October 15, 2012
*** Two-Day Hands-On Workshop on WarpPLS: SEM Fundamentals with Linear and Nonlinear Applications ***
Structural equation modeling (SEM), or path analysis with latent variables, is one of the most general and comprehensive statistical analysis methods. Path analysis, multiple regression, ANCOVA, ANOVA and other widely used statistical analysis methods can be seen as special cases of SEM.
WarpPLS is a very user-friendly and powerful software tool that can be used for SEM, arguably being the first of its kind to implement linear and nonlinear algorithms. This software provides one of the most extensive sets of SEM outputs; among other things it is the first of its kind to automatically calculate indirect and total effects and respective P values, as well as to calculate full collinearity estimates.
This SEM fundamentals workshop (details below) is designed to be useful to beginners and intermediate SEM practitioners. Among possible participants are those who are interested in: (a) being productive co-authors or research collaborators, even if not doing SEM analyses themselves; (b) conducting basic SEM analyses occasionally in the future; (c) conducting SEM analyses of intermediate complexity on a regular basis.
*** Registration and additional details ***
*** Instructor ***
Ned Kock, Ph.D.
*** Location and dates ***
Our Lady of the Lake University
San Antonio, Texas
11-12 January 2013 (Fri-Sat), 8 am–5 pm
*** Workshop program at a glance ***
The main goal of this workshop is to give participants a practical understanding of how to use the software WarpPLS to conduct variance-based SEM. The workshop is very hands-on and covers linear and nonlinear applications.
Day 1 of workshop
• Overview of workshop and formation of teams
• Overview of web resources: Video clips, blog, publications, spreadsheets, and templates
• Overview of steps 1 to 5 of a complete SEM analysis
• Hands-on exercise: Complete SEM analysis
• Resampling as shuffling multiple decks of cards
• Choosing the right resampling method
• Hands-on exercise: Resampling options
• Choosing the right warping (i.e., nonlinear) algorithm
• Viewing and interpreting plots of linear and nonlinear relationships
• Hands-on exercise: Linear and nonlinear relationships
• Charting non-standardized data
• Reporting results in non-standardized terms
• Hands-on exercise: Standardized to non-standardized results
• Reading discussion: WarpPLS User Manual
Day 2 of workshop
• Classical tests of mediating effects – Baron & Kenny and Preacher & Hayes
• Using indirect and total effect outputs to test mediating effects
• Hands-on exercise: Indirect/mediating and total effects
• Reading discussion: Kock & Verville’s free questionnaire data article
• Testing a moderating effect
• Double, triple etc. moderation
• Hands-on exercise: Moderating effects
• Adding control variables into an analysis
• Using second-, third- etc. order latent variables
• Conducting a multi-group analysis
• Hands-on exercise: Multi-group analysis
• Reading discussion: Kock & Lynn’s lateral collinearity article
• Conducting a full collinearity test
• Hands-on exercise: Team project using participant’s own data
• Presentation of results from team project
Wednesday, March 7, 2012
Thursday, March 1, 2012
New article discussing methodological issues based on WarpPLS: Exploring free questionnaire data with anchor variables
A new article discussing methodological issues based on WarpPLS is available. The article is titled “Exploring free questionnaire data with anchor variables: An illustration based on a study of IT in healthcare”. It has been recently published in the International Journal of Healthcare Information Systems and Informatics. See this post on the WarpPLS blog for more details and a link to a full text version of the article.
Monday, January 23, 2012
Version 3.0 of WarpPLS is currently undergoing a battery of tests, and will be made available soon. Among the new features is the calculation of indirect and total effects, which are exemplified in this health data analysis post based on the China Study II dataset. Check this post for a comprehensive list of new features in this version.