Hi all
I have data from a randomized trial that measures the effect of an intervention group (0/1) on a biomarker outcome measured at 3 time points (0hr, 12hr, 24hr). I have constructed the below model to assess whether there is any difference in change in the biomarker outcome over time by group. The biomarker is log transformed as it is not normally distributed.
mixed log_biomarker group##i.time || StudyID: studysite, cov(exch)
The output gives me a significant interaction effect at the 24 hour time point with a coefficient of 0.3 and p-value of 0.04.
I understand this means that there is a difference in the trajectory of the biomarker between group with respect to time. What I'm not clear on is how to report this coefficient. Is it fair to exponentiate it ~1.4 and say that a change in group results in a 40% difference in slope over time? Is there a way to use margins here?
Thanks in advance for any suggestions!
Related Posts with Help interpreting longitudinal mixed model interaction term
Large variances in probit regressionHi, I encountered the following problem when running IVPROBIT: the regressors include a few dummy v…
Testing some stuff Code: sysuse nlsw88,clear reg married i.collgrad##c.wage margins collgrad, at(wage== (5 10 15)) po…
Split string variables with numeric valuesHi, I am using Stata 17 and need some help with splitting of string variables. Below is an example …
Linear probability models with interactions: how can I calculate relative effects / relative risk ratios?Dear Statalisters, I am running Linear Probability Models with interactions and would like to calcu…
Having Two Margin Plots on One GraphHi everyone. I am struggling with a presentation issue. I have run a probit regression and I am coll…
Subscribe to:
Post Comments (Atom)
0 Response to Help interpreting longitudinal mixed model interaction term
Post a Comment