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I have a random intercept and random slope mixed linear model with a continuous dependent variable. To calculate ICC, proportion of dependent variable explained by model with predictors at Level-2 and Level-1 I produce "intercept only" Null Model 1 and Null Model 2 (random intercept and random slope, i.e. with time included).

1) Does Intercept-Only Null Model 1 intercept variance .412*** (.089 SD) set the limit on proportion of dependent variable explainable at Level-2 by the full model with predictors and random slopes and intercepts 1.700*** (.378 SD)?

2) Specifically what I am asking: is that .412* intercept variance the only explainable at Level-2 part of 1.700* intercept variance**** in the full mixed-effects model?

Because if I try to compute proportion of dependent variable variance explained at Level-2 by the full model using the formula from Sampson and Bryk (2002, p.74) (intercept variance Null model – intercept variance Model with Predictors) / intercept variance Null model I get = 3.1 i.e. more than 1 or more than 100% (and that never happened in my experience). Is that 3.1 proportion of explained dependent variable variance an anomaly?

3) Should I use Intercepts and Slopes Null Model 2 as the baseline (not Null Model 1) to compare full models with random intercepts and slopes and predictors for ICC, L-1, L-2 calculations with intercept variance 1.713*** (.372)? But that boosts ICC to .79.

I would appreciate any insight!

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