Course content
Mplus is a statistical modeling program that provides researchers with an extremely flexible modeling framework. It allows the analysis of both cross-sectional and longitudinal data, single-level and multi-level data that may come from multiple populations, and data with missing values.
This course provides an introduction to Mplus for individuals who wish to use this software program for their data analysis requirements.
Topics covered include:
- Introduction to Mplus
- Path Analysis with Mplus
- Factor Analysis with Mplus
Course format/structure
Course delivery includes voiceover Power Point information, associated reference guides, web links and the opportunity to practice Mplus procedures using a training data set accessed through Population Data BC's Remote Training Lab (RTL).
Training time
The self-paced course is divided into 3 modules. Each module can be reviewed in approximately 12 to 20 minutes with a total training time of approximately 40 minutes. Additional practice time using Mplus software and the training data set within the Remote Training Lab is open to your individual needs. There are no set exercises, instead you are encouraged to practice the specific activities outlined in the Mplus modules you have just reviewed.
You may wish to complete the modules all together or as separate training sessions over a period of several days or weeks to best fit your schedule or learning preferences.
Access fee
Access to this guide is free. Go to: my.popdata.bc.ca and, if you do not already have a my.popdata account you will need to sign up and create one.
Once you have a my.popdata account, go to the Education & Training section of the my.popdata site at https://training.popdata.bc.ca/. You can then login in with your PopData account username and passphrase and self-enroll to access the guide/course.
Course presenter
Rubab G. Arim, is a Methodologist at the Ottawa Hospital Research Institute and an Adjunct Research Professor in the Child Studies program at Carleton University. Dr. Arim has experience working with Mplus in longitudinal research using large-scale population-based data.
