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Level 2 predictors on level 1 outcome |
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I am trying to run multi-level regression analyses, with children nested within preschool rooms. My primary question is the extent to which a level 2 variable (measured at the room level) predicts a subsequent level 1 outcome (measured at the child level). There are also important covariates that I need to control for at both the room level and child level. I have tried to put together this model – see script below, which I have simplified for the purpose of illustration – but am getting a number of error messages. Are you able to advise what I am doing wrong? Data: File = DATASET.csv; Variable: Names = Room ! Room is cluster variable RoomCov1 ! Room-level covariate (categ.) RoomCov2 ! Room-level covariate ChldCov1 ! Child-level covariate (categ.) ChldCov2 ! Child-level covariate ChildY ! Central child-level outcome RoomX1 ! Central room-level predictor RoomX2; ! Central room-level predictor Usevariables = Room RoomCov1 RoomCov2 ChldCov1 ChldCov2 ChildY RoomX1 RoomX2; Missing are all (-999); Cluster = Room; Analysis: Type = twolevel; Estimator = ML; Model: %Between% ChildY ON RoomCov1 RoomCov2 RoomX1 RoomX2; %Within% ChildY ON ChldCov1 ChldCov2; Output: Tech1 standardized sampstat; |
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You have to put room-level covariates on the Between= list. See UG examples such as 9.1 |
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