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Hello Forum members,

My question is theoretically very trivial but somehow I cannot realise it in MLwiN. Let´s assume I have a two-level model.
I have my constant as well as Level 1 predictors that are allowed to be random at Level 2. This results in the respective Level 2 equations of these parameters to which I would like to add further Level 2 variables. However, in MLwiN each variable first appears at Level 1. If I let this variable go random it gets its own Level 2 equation which is not my goal. If you have a solution for this I would highly appreciate it!

Thanks very much,
Jake

Unlike some software (such as HLM), MLwiN has level 2 variables in the main equation. If they are really level 2 variables, they will show with a j subscript, and not an ij subscript, as they are constant at level 2. If they do not show as j there is probably something wrong with the sorting of the variable and you can check this by looking at the variable in question and the level 2 indicator variable, they should only change in harmony.

If you want to use a higher-level variable to try and explain the random slopes associated with a level -1 predictor, you first need to create a cross-level interaction between the level 1 predictor and the level 2 group variable. [ In the equations window - add term - order 1 and then add both the level 1 and level 2 variables as an interaction - the new variable will then have the ij not j subscript]

Chapter 6 of the User manual deals with this and the inclusion of the higher level variable is known as estimating 'contextual' effects

Thank you very much for your swift reply and your time!

This was exactly what I was looking for and yes my basis for comparison was indeed HLM.

I wish you a nice weekend,
Jake