This course provides a thorough and comprehensive overview of Bayesian psychometric modeling.
It presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. This course explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The course starts with simple models and then builds from them to develop more complicated models. Throughout the course, procedures will be illustrated using examples primarily drawn from educational assessments. The course will use Mplus/Stata software packages.
It presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. This course explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The course starts with simple models and then builds from them to develop more complicated models. Throughout the course, procedures will be illustrated using examples primarily drawn from educational assessments. The course will use Mplus/Stata software packages.
- Teacher: Rehab Al Hekmani
- Teacher: Shaljan Areepattamannil
- Teacher: Patricia Fidalgo
- Teacher: Ieda Santos
Skill Level: Beginner