This course will provide you with an introduction to—and hands-on experience specifying—multi-level modeling and longitudinal analysis. You will gain an understanding of different types of approaches including:
time varying and invariant predictors
multivariate and multi-population models with different outcomes
missing data, errors in measurement and measurement misclassification
This course is designed to serve the needs of researchers who will analyze and model longitudinal data in population health research.
Define the methodological features of longitudinal data analysis.
Describe fundamental concepts and issues in multi-level modeling.
Identify different analytical approaches to longitudinal data analysis and specify their strengths and limitations.
Use Mplus statistical modeling program to perform longitudinal data analyses in population health research.
Develop and practice longitudinal model specification, estimation, evaluation, and modification skills.
Interpret and evaluate findings in longitudinal population health research.
This course may be available online. Students login to the course and communicate with the instructor and fellow students via the Internet. All assignments and course activities are submitted electronically to the course instructor.
Using mobile devices in online courses
If you are planning on accessing your online courses using a mobile device such as a tablet or a smartphone, please note that not all required course features will be accessible with these devices. To fully function in your online courses, you will need to have access to a computer running Windows or MacOS.
Tuition will be fully refunded (less a $100 administrative fee) with written notice to Maxine Reitsma (email@example.com) by 11:55 pm, six calendar days after the official course start date. A 50% refund will be provided with written notice by 11:55 pm, 13 calendar days after the official course start date. No tuition refunds will be provided after this date.