Cross-sectional data - MLM
9 important questions on Cross-sectional data - MLM
How do you compare the variances of 2 models with eachother when you want to use variance to explain the differences in outcome between clustervariables?
model 2 = add variable to fixed part + random intercept (1 cluster variable)
(variance model 1 - variance model 2) / variance model 1 = % of the difference in outcome variable between clusters explained by the variable added.
How do you use ICC as indicator of explained variance? 2 steps
2. Determine the ICC
What is the formula for ICC with linear regression?
Var (_cons) is between variance
Var (_cons) + var (residual) = total variance.
so between variance/total variance
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What is the interpretation of using variance as explanation? (model 1 random intercept only model, model 2 random intercept + determinant)
Why dont you have a residual variance with logistic regression?
How do you use variance as an indicator?
2. Write down the variance of random intercept cluster 1
3. Make a model 2 with cluster on 2 levels
4. Write down the changed variance of random intercept cluster 1
5. Compare the changed variance
What is the formula for variance as indicator?
What is the interpretation when variance is used as an indicator? So when for example variance in neighborhood goes down by adding another level of clustering(country)?
so then you can say (when you for example have 70%), most of the explanation is not because of neighborhood but because of country.
Why is the residual variance higher when you have 2 levels of clustering in stead of 1?
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