Cross-lagged panel model with random intercept in MATLAB

Hello,

I am getting started with cross-lagged panel models, I would like to implement a cross-lagged panel model with random intercept (RI-CLPM) to my data, but I'm struggling to find a way to do it in Matlab. Are you aware of any toolbox/function that would allow me to do/build that? I am sorry if this is a too general question, but any insights on this would be really helpful.

Thank you very much in advance!

Laura

Answer 1

[Anshuman]

Hi Laura,

In MATLAB, there is no specific toolbox or function dedicated to implementing cross-lagged panel models (CLPMs) with random intercepts. However, you can use MATLAB's statistical modeling capabilities and optimization functions to build and estimate such models. What you can do is :

1. Start by defining the structural equations that represent the cross-lagged relationships between variables in your model.
2. Convert the model equations into an optimization problem that can be solved using MATLAB's optimization functions. This typically involves formulating the problem as a maximum likelihood estimation (MLE) problem.
3. Write a MATLAB function that calculates the likelihood of the observed data given the model parameters.
4. Use MATLAB's optimization functions, such as 'fmincon' or 'fminunc', to estimate the model parameters by maximizing the likelihood function.
5. Assess model fit and interpret results.

Hope it helps!