Webinar “Structural equation modelling with Mplus”
Marian Vasile, Associate Professor
University of Bucharest, Faculty of Sociology and Social Work, Department of Sociology
Date: 28 March 2022
Duration: 2 hours
Time: 11:00 —13:00 Romanian time (UTC + 3 hours), 10:00-12:00 Norway time (UTC + 3 hours)
Platform: ZOOM (registration is required)
During this webinar, you will learn the basic input for structural equation modelling (SEM) in Mplus. Applications refer to social exclusion in old age. We will discuss the elementary concepts for SEM and how can we translate them into a working empirical model. SEM combines at least one measurement model with a structural model. A measurement model implies at least one latent variable and several observed indicators. We test measurement models with confirmatory factor analysis. A structural model implies at least one dependency between two variables, observed / latent / observed-latent. All models use individual level and cross-sectional data from international comparative surveys.
You will receive:
SPSS syntax file for data cleaning
Mplus input file for SEM
This is a hands-on workshop. We will use IBM SPSS Statistics (SPSS) and Mplus. In SPSS we will clean and prepare the data for Mplus. In Mplus we will write the syntax for SEM, run the models, and interpret the results.
You can download a 30-day trial of SPSS from this link . You can replace SPSS with PSPP, which can be downloaded from this link , but you will make all the procedures from the menu, and you will not receive the syntax files. If you are familiar with other statistical software (e.g., R, Stata) you can use them.
You can download a demo version for Mplus from this link . We will use Mplus 8.6 version.
Familiarity with data cleaning, exploratory factor analysis, and regression analysis will be a plus during this webinar.
Please, have SPSS and Mplus installed on your computers! If you need help with installation, please contact me before the workshop at email@example.com.
- 11:00-11:30 concepts
- 11:30-12:00 data cleaning in SPSS and preparation for Mplus