1. I am working on some research relative to females unemployment, and want to use the Multilevel Modelling techniques, but when my residual variance is .043 for an empty model, I include some explanatory variables for level-1 then it would increase. Now, I could not interpret it. Please guide me how to interpret it, and also if it becomes smaller, then whether it would be better off if it increases.
Some results are attach for your information.
2. Is there any criteria for the selection of the explanatory variables to be included for level-2 ?
Indeed this does happen in multilevel models.
See here
http://andrewgelman.com/2006/05/15/in_a_multilevel/ for an explanation by Andrew Gelman
And a link to the relevant pages in his book: http://www.stat.columbia.edu/~gelman/stuff_for_blog/adding.pdf )
Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.
Section 4.1 of Joop Hox's book gives an analysis strategy and can be used for the decision which explanatory variable to include.
Re question 2, I follow the procedure described in Zuur et al. (2009).
Zuur, A., Ieno, E. N., Walker, N., Saveliev, A. A. and Smith, G. M. (2009). Mixed effects models and extensions in ecology with R, Springer.
- Badges
- Science topic
- Similar topics
- Mathematics
- Statistics
- Statistical Techniques