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
F test xtreg, fe indicates pooled OLS is better. What are the consequences for fe?Hello, I am running a fixed effects model on an unbalanced dataset. I cannot reject the null hypoth…
Replace missings in an unbalanced panel CONDITIONAL on year and firm IDHello everyone, I am new to Statalist and have an issue with filling up missings in a panel data set…
Correcting autocorrelation by adding year dummy variables?Hello everybody! For my master dissertation, I'm dealing with panel data. In addition, I detected h…
unbalanced pandel data model - assumptionsHello, I have a clustered model which I run regress on unbalanced panel data. I am not sure which …
Small N and large T panel analysisHi! I am using panel data with N=6 and monthly data from 2000 to 2017 i.e., T=216. The specific indu…
Subscribe to:
Post Comments (Atom)
0 Response to Help interpreting longitudinal mixed model interaction term
Post a Comment