Does it make any sense and is it even possible to examine the impact of a level-1 independent variable (e.g. student gender) on a level-2 dependent variable (e.g. mean performance), which is an aggregated variable.
When I try this with Analysis: type = TWOLEVEL, the output state:
THE VARIANCE OF 'mean perfomance' APPROACHES 0. FIX THIS VARIANCE AND THE CORRESPONDING COVARIANCES TO 0, DECREASE THE MINIMUM VARIANCE, OR SPECIFY THE VARIABLE AS A BETWEEN VARIABLE
Any variable that does not vary within clusters must be put on the BETWEEN list. These variables can be used only in the between part of the model. A variable measured on the individual level can be used in both parts of the model if it is not placed on the WITHIN list. In this way you could regress a between variable on the between part of a within variable. See Examples 9.1 and 9.2 for further information.
Jana Nie posted on Wednesday, June 08, 2011 - 3:47 am
Dear Ms Muthen,
is it possible to use a level 2 dependent variable if I first aggregate (mean) the data on that level two variable?
I understand that multilevel regression cannot accommodate level 2 outcomes. Without thinking, I ran the following model and am now wondering why it worked. I have not modeled any latent variables. Therefore this is multilevel regression with a level 2 outcome and not structural regression? What am I missing?