Latent State-Trait Modeling
with Mplus
Learn how to analyze, interpret, and report LST models with Christian Geiser's on-demand course
Latent State-Trait Modeling with Mplus uses Christian Geiser's video-based instruction in combination with associated datasets, syntax, and a workbook to form a solid foundation for performing a variety of LST analyses. The course is broken into 11 sessions that can be completed in about 2 days, though the timing in which you work through the course is entirely up to you. Use the dropdown menu below to see what's included:
Welcome to this Course!
FREE PREVIEWHandouts, References, & Resources
Introduction to Latent State-Trait (LST) Theory
The Latent State (LS) Model
The LS Model & Measurement Equivalence Testing in Mplus
The LS Model with Indicator-Specific Factors
FREE PREVIEWThe Singletrait-Multistate (STMS) Model as Hierarchical Factor Model
The STMS Model Specified as Bifactor Model
Accounting for Indicator-Specific Effects in LST Models
Introduction to LST Models with Autoregression
LST Models with Autoregression in Mplus
Overview: Other LST Approaches
Tips on How to Report the Results
Thank You and Final Tips
Dr. Christian Geiser
Dr. Christian Geiser is a Professor of Quantitative Psychology at Utah State University, author of two books on Mplus, and a leader in the development of latent variable techniques for complex data. With his accessible books and sought-after workshops, he has helped thousands of researchers and students around the world to achieve their analytic goals. This course is part of a companion series of workshops to his books and articles.
Tax-exempt institutions in the United States, please start here.
Latent State-Trait Modeling with Mplus is available for immediate access. Please contact us if you need an invoice prior to purchase or have a larger group.
Payment is accepted by credit card, Paypal, or bank transfer (euros & GPB). Bank transfer instructions are here.
Group licenses provide the lowest per-person cost.
Further discounts are available for researchers working in LMICs; apply here to get started.
Individual: Student/Post Doc
Individual: Professional
Lab | Up to 6 Users
Bank transfers are accepted in euros and GBP. Please contact us if your bank is outside of the EU, SEPA, or UK.
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euros (EU & SEPA only) |
GBP (UK only) |
Student/Postdoc: €217 Professional: €272 Group: €707 Account holder: QuantFish LLC BIC/SWIFT: TRWIBEB1XXX IBAN: BE20 9672 6025 0356 Address: Avenue Louise 54, Room S52 Brussels 1050 Belgium Required notes:
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Student/Postdoc: £182 Professional: £228 Group: £595 Account holder: QuantFish LLC Sort code: 23-14-70 Account number: 87960744 IBAN: Address:
56 Shoreditch High Street, London E1 6JJ, United Kingdom Required notes:
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Absolutely. You can engage in the full curriculum using only the demo version of Mplus, which is FREE. Dr. Geiser will provide instructions about getting the demo installed on your computer.
This course is for learners with foundational knowledge of confirmatory factor analysis. A working understanding of the Mplus software is helpful, but not required. Need a beginner-focused course? Mplus from Scratch gives you everything you need to be ready for this workshop.
We understand completely! The timing is entirely up to you. Once you enroll and the course has launched, you will have unlimited access to the content. You are free to pause and return to your lessons as needed.
Dr. Geiser is happy to answer questions related to course content and Quantfish promptly resolves any technical issues related to the course platform. If you are interested in personal consultation on your own data, please contact us to get started.
Try a free preview of our Mplus courses:
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Learn how to use Mplus simulations to plan your sample size in this free mini-course!
New courses are always coming! Add your email to our list to get the latest updates.
QuantFish is dedicated to providing courses that improve your analytic skills with accessible lessons from the world's leading methodologists. Latent State-Trait Modeling with Mplus is backed by a complete money-back guarantee for 7 days following the start of the course.