Setting up an AR(1) model
Posted: Mon Mar 30, 2020 7:24 pm
Hi Chris, George, and all,
I hope everyone is doing well.
I have a question about setting up and running a growth curve model that has the additional wrinkle of allowing for an AR(1) structure to the residuals. I have looked at the MCMC manual, chapter 19, and seen the example with the rats dataset. That example is different because the data is in a wide format, with each measurement getting its own column. Is that how the data has to be setup to use the corresiduals() option? Or can it also be used when you have your data setup as long?
For reference, this is the model I am currently running (data is in long/stacked format with 4 unique values of yr):
I used the reflated residuals at level 1 to investigate residual correlations and see larger than expected autoregressive correlations that I would like to account for.
Thanks!
I hope everyone is doing well.
I have a question about setting up and running a growth curve model that has the additional wrinkle of allowing for an AR(1) structure to the residuals. I have looked at the MCMC manual, chapter 19, and seen the example with the rats dataset. That example is different because the data is in a wide format, with each measurement getting its own column. Is that how the data has to be setup to use the corresiduals() option? Or can it also be used when you have your data setup as long?
For reference, this is the model I am currently running (data is in long/stacked format with 4 unique values of yr):
Code: Select all
runmlwin (sel cons yr yr_sq, eq(1)) (math cons yr yr_sq, eq(2)), ///
level2(id: (cons yr, eq(1)) (cons yr, eq(2)), residuals(uq, reflated)) ///
level1(obs: (cons, eq(1)) (cons, eq(2)), residuals(rq, reflated)) nopause corr
Thanks!