0
$\begingroup$

I am interested in the modelling of time-varying predictors in a multilevel growth model in R.

Specifically, I am working with three-level data (measures collected across four timepoints (0,12,18,24 months) on pupils nested within schools). I am interested in exploring the extent to which a time-varying predictor (a school characteristic) can explain outcome variance at the pupil- and school-level (my outcome is measured on a continuous scale).

I am now wondering how I could introduce this time-varying predictor in my models? (I am running my analyses in R version 3.6.2.; and I use the R package 'lmer' to fit my multilevel growth models). I assume introducing each measure of the time-varying predictor (at 0-24 months) as a separate predictor in the models would not be appropriate?! Hence, I wonder whether I could reshape the data into the long format to not only have my outcome and time represented by one variable but also this time-varying predictor? I could then use this one variable of my time-varying predictor (which summarises in the long format all measures across time) to predict my outcome? Would this be appropriate? Or is there any other way to model time-varying predictors in this context?

Also by doing it this way (modelling the time-varying predictor in the long-format) would I then be able to examine the longitudinal relationship between the time-varying predictor and the outcome over time or would the estimates represent the cross-sectional relationship (i.e., for each assessment wave the relationship between the time-varying predictor and the outcome at that point in time)?

Any advice would be very much appreciated.

New contributor
Verena Hinze is a new contributor to this site. Take care in asking for clarification, commenting, and answering. Check out our Code of Conduct.
$\endgroup$

Your Answer

Verena Hinze is a new contributor. Be nice, and check out our Code of Conduct.

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.