### Three-level model with two random slopes

Posted:

**Mon Nov 30, 2020 11:56 am**Dear all

I am trying to fit a (nested) three-level model with a three-way interaction, where there are constituent terms of the moderation at all three levels.

i.e. the response is observed at level 1 (binary), moderator1 at level1, moderator2 at level2, and moderator3 at level3. Moderators1 and 2 are group mean centered at level 3.

Now, I would want to allow the slopes of moderator1 and moderator2 to vary at level 3.

While it works with the diagonal restriction

once I take the diagonal restriction out -which I would want-
The result is that cov(cons,S), cov(F,S), and var(S) are returned as 0.

Thank you very much in advance!

I am trying to fit a (nested) three-level model with a three-way interaction, where there are constituent terms of the moderation at all three levels.

i.e. the response is observed at level 1 (binary), moderator1 at level1, moderator2 at level2, and moderator3 at level3. Moderators1 and 2 are group mean centered at level 3.

Now, I would want to allow the slopes of moderator1 and moderator2 to vary at level 3.

While it works with the diagonal restriction

Code: Select all

`runmlwin DV cons c.L##c.F##c.S level3(level3: cons F S ,diagonal ) level2(level2: cons) level1(level1) discrete(distribution(binomial) link(logit) denom(cons)) nopause or zratio maxiterations(50000)`

once I take the diagonal restriction out -which I would want-

Code: Select all

`runmlwin DV cons c.L##c.F##c.S level3(level3: cons F S ) level2(level2: cons) level1(level1) discrete(distribution(binomial) link(logit) denom(cons)) nopause or zratio maxiterations(50000)`

- How can I recover these parts of the model?

Thank you very much in advance!