### homoscedasticity assumption in logistic models?

Posted:

**Fri Mar 03, 2017 7:13 pm**Hi

1)

It is usually suggested that it is not meaningful to check the homoscedasticity assumption in single level logistic models because the outcome is binary, but is it meaningful to check homoscedasticity on the log-odds scale? Probably the answer is still no, since one does not assume homoscedasticity at all, right?

2) Is homoscedasticity assumed for the second level variance?

I plotted “the standardised residual x fixed part prediction” for the second level, and wonder if it shows anything meaningful for you?

3) in terms of model assumptions, is the 95% residual-rank plot used for anything specific? That is, more than checking some clusters are deviating from the mean estimate and warranting the need for a multilevel model.

Thanks in advance

1)

It is usually suggested that it is not meaningful to check the homoscedasticity assumption in single level logistic models because the outcome is binary, but is it meaningful to check homoscedasticity on the log-odds scale? Probably the answer is still no, since one does not assume homoscedasticity at all, right?

2) Is homoscedasticity assumed for the second level variance?

I plotted “the standardised residual x fixed part prediction” for the second level, and wonder if it shows anything meaningful for you?

3) in terms of model assumptions, is the 95% residual-rank plot used for anything specific? That is, more than checking some clusters are deviating from the mean estimate and warranting the need for a multilevel model.

Thanks in advance