Hey everybody, as discribed above, I'm working on my final master thesis
including multilevel analysis with 3 metric group-level variables. I've got 6 ML-models
1.empty model
2. random intercept with individual level fixed effects
3. Random intercept model with individual- und group-level fixed effects
4 Random slope model mit individual-level fixed effects
5. Random slope model with individual- und group level fixed effects und cross-level interaction
6. Random intercept model mit individual- und group-level fixed effects und cross-level interactions
So this is my first multilevel analysis and the results rised some questions:
Model 3 produced only not significant group level effects.
Model 5 produced one significant and two not significant (p>|z|=>0.05) group variables, the cross-level-interactions
showed: two are significant, one isn't. One of the significant cross-level-interactions is also the only significant group level variable.
So, how to interpret these findings?
And what does it mean that a group-level variable is not significant but the cross-level interaction still is?
Hope someone can help me
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