Two-level multilevel model using SPSS (chapter 3 v3); predicting variation in intercepts in HLM

This is the third of several videos illustrating how to carry out multilevel modeling involving two levels. It specifically addresses how to predict variation in random intercepts in HLM through the inclusion of Level 2 predictors.

[delial]

Hi Mike! Thanks for the video. Im wondering how do you get an estimate of effect size from the SPSS output for this model?

[harapodcast]

thanks a lot.
we need more on categorical response variable.

[hannesrosenbusch]

Hi Mike, great video series! I wonder why you did not center the ses predictor (variable "ses") within schools. I understand that the variable "ses_mean" represents the school level ses, but if you want to disagregate school level and individual level effects of ses (i.e. see if they are BOTH significant), is it not usually the case that you have to group-center the individual level ses variable, before putting both predictors in the same model?

[DB-inmr]

Mike,
I run with your approach here, but with a mixed model operating at L2 level only with 4 L2 predictors...and no use of L1 predictors. Kept a L1 target...what's your opinion?...clearly it works technically, but wondering about theoretical consistency of this ...

[aparnasm]

hii..thank you so much for the video.. i had a doubt with respect to control variables at level 1 and level 2. how should we treat them?

[christoph]

Thanks so much for this video - helps a lot! In my dataset, I have fixed effects of variables which have a quite different scale, so it's hard to compare the Estimates of Fixed Effects. Would you know if there is a way to automatically show standardised fixed effects (like the "beta" in an ordinary regression model)?

[dawitmuluneh]

thanks for your interesting presentation and i will have measurement seminar presentation on GLMM. i don't know how i can get multi level longitudinal row data for my seminar demonstration?can you guide me the way?thank you