Kai Rödiger posted on Monday, September 30, 2013 - 2:29 am
Dear Linda and Bengt,
I'm quite new to MPlus and Multilevel Modelling but I figured out most of the basic stuff quite well. Now I have serious problems with a Cross-Level Interaction and need your help to know if it is possible at all to have a model like this.
So in short: I have LVL 2 measurements at the employee lvl (customer attitude) and LVL 1 measures at the customer LVL (perception of behavior).
I want this path to be moderated by the age difference between employee and customer modelled by (AE - AC). Each employee has up to 3 matched customers so there are up to 3 different values for Delta Age.
--------------------------Delta Age (I think this has to be a Within-Variable) -----------------------------| -----------------------------| -----------------------------| -----------------------------v Employee Behavior (L2) ----> Customer Perception (L1)
I tried various ways to define the slopes in the within and between part of the model but none of them worked out. Could you give me a hint if at all (and if yes how) such a relationship can be modelled?
Best regards and thank you very very much in advance, Kai
In multilevel modeling, you can't have a random slope on the highest level.
Kai Rödiger posted on Monday, November 25, 2013 - 3:02 am
thank you very much for your response. Do you have any suggestion how to solve this problem? Which method / approach might be best if cross-level interactions won't work here. Is a multilevel multigroup analysis a valid approach for this problem?
Yanxia WANG posted on Thursday, March 19, 2015 - 7:44 pm
I am new to Mplus, and recently met a similar problem which the level 2 moderator moderates the relationship between independent variable from level 2 and dependent variable from level 1. I did what Linda suggested, however, Mplus reported error with undefined zw (the interaction item). I really could not figure it out. Would you please help me to handle with this problem?
Bep Uink posted on Thursday, December 03, 2015 - 6:10 pm
Hello, I am running a 2 level model in the uni variate format, with experience sampling data. I am trying to predict an outcome at time 1, controlling for a co-variate a t-1. However, I do not want between-day lags (i.e. I do not want participants ratings in the morning to be predicted by their last rating on the previous day). However, I am not sure the syntax for this? I have thought of excluding observations the occur in the first time point of the following day, but these are are also used as t-1 covariates for the following time point. Any help would be very appreciated. Thank you.
You can consider three level modeling where the middle level = day. Alternatively and probably the easiest is to have 0 for that covariate in the data for the first observation in the day.
Bep Uink posted on Sunday, December 06, 2015 - 10:09 pm
Thank you, Tihomir. I am not clear on what covariate. To be more clear, I am trying to regress mood at time 1 onto event at time 1, controlling for mood at t-1. Because I do not want events from the previous nights' time point predicting the next mornings' mood, should I replace data for night time events with 0?
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