Contents
What is cross-level interaction?
A cross-level interaction is just an interaction where one of the predictors is restricted in its variability to units at level 2. If the model makes sense then go ahead. It is however not uncommon for a random slope to be an equally good explanation (in terms of model fit) to a model with the cross-level interaction.
What is cross level analysis?
Broadly defined, cross-level inference occurs when. relations among variables at one level are inferred. from analyses performed at a different level. A. straightforward example would be the use of depart-
How to use interaction terms in fixed effects model?
Interaction terms in fixed-effects model. The fixed-effects don’t really change anything, except that if one of the variables, say X2, is constant within each firm, the X2 main effect will be collinear with the fixed effects and will be automatically dropped from the regression. Yes, you can do all this in -xtreg-.
How is a time effect different from a fixed variable?
This is different from added a time effect to your model, as such a ‘time’ variable is averaged over the entire population, instead of the value of another variable. An example with some graphics will help: imagine you would predict annual income ( y) over time ( T, (age) years) with gender ( X 1; 0=male, 1=female) as predictor variable.
How does the effect of an interaction change over time?
As you can see in the first graph, the effect (difference between the two lines) of gender is constant, while in the second, the effect changes over time. That is the effect of such an interaction term and the reason some add it.
When to look at interactions with time specifically?
So when looking at interactions with time specifically, basically what you are saying is that some variables’ effect on the outcome is allowed to change over time. This is different from added a time effect to your model, as such a ‘time’ variable is averaged over the entire population, instead of the value of another variable.