Hi,

I collected data from an experience sampling study over 14 days, where participants belonged to five different batches (done for convenience, and was not a test variable), and responded to the same questionnaire five times each day of the 14 days. I'm building models to predict for eg sleep from phone use, and have the following syntax:

mixed sleep phone_use || _all: R. Questionnaire_number || _all: R. ID || Batch_No: || Study_day_number:

(questionnaire number and participant ID are crossed because each participant responded to all five questionnaires every day; study day number i.e. 1 to 14 is nested within batch number because the study was conducted over different days for participants belonging to separate batches).

a) Can anyone share shed some light regarding the way I've built up my syntax? I'm a bit lost regarding the use of four levels in a crossed effects model, any advice would be helpful! and b)What sort of post estimation analyses can I conduct to verify that the model is doing what I've asked it to do, eg robustness checks etc?

I must mention that the models are converging, but I just want to make sure that they are the correct models and verify the output.

best wishes,
Ahuti