Cross lagged panel design is a type of longitudinal structural equation model where information is collected at two or more points in time. It’s used primarily to assess causal relationships (which may potentially be bi-directional) in a non-experimental setting, i.e., where variables are not manipulated but simply recorded.
Carry out different types of longitudinal invariance assessments such as:
a. Configural invariance b. Metric invariance c. Scale invariance d. Residual variance invariance, and e. Residual covariance invariance
Imposing equality constraints on structural model elements such as:
a. Disturbance variances, b. Autoregressive effects, and c. Cross-lagged effects
Perform Chi-square difference tests
Assess the stability of variables over time
Determine the causal direction between variables (i.e., directional and reciprocal relationships)
Evaluate the relationships between changes in variables over time
Requirements
A good understanding of cross-sectional CB-SEM methods is required to better understand the longitudinal analysis (basic issues are not explored in this workshop).
Participation in our EQS 6.4 workshop (October 12-13, 2022) is encouraged: Here is the registration link: https://forms.gle/UjhcVciMZPJXVrrv7
Watching the videos on CB-SEM analysis with EQS through the channel below is encouraged:
Audience
Social sciences and medical researchers, R&D experts from industries, as well as post graduate students who are interested in advanced longitudinal statistical analysis may find this workshop meaningful and relevant.
