Hi,
I'm using Stata 12IC for Windows. I'm trying to perfom multilevel mixed effects modelling on a dataset where there are 2 groups of samples (id) defined by GRP (1/0). I have made repeated measurements on these samples to obtain the dependent variable OUT, at increasing concentrations of a drug (CONC 0-5) (CONC was increased sequentially at each timepoint, therefore this variable serves as both timepoint and concentration). I am treating CONC as a continuous variable here. I have chosen to have GRP as an explanatory variable/fixed effect as there are only 2 possible groups.
I have used the following command for a random slopes model:
Please see attached pictures of the graph for the mean responses of the two groups, and the output from this command. I would be grateful for help in checking I have understood the output correctly. Am I correct in thinking the following (referring to coloured circles)?
1 (red): the intercept of GRP0 at CONC 0
2 (green): the p-value for null hypothesis that there is no difference between GRP0 (the reference) and GRP1. This indicates the null hypothesis should be rejected: there is a difference. But is this just at baseline, or across all concentrations?
3 (blue): I am not sure here. Is it the p-value for the null hypothesis that there is no difference in OUT across all concentrations, but for both groups combined? And as it is <0.05, this suggests OUT does vary with CONC in some way?
4 (purple): p-value for the interaction - highly significant, suggesting there is an interaction and that OUT varies with CONC differently for each group
Thanks
Jem

I'm using Stata 12IC for Windows. I'm trying to perfom multilevel mixed effects modelling on a dataset where there are 2 groups of samples (id) defined by GRP (1/0). I have made repeated measurements on these samples to obtain the dependent variable OUT, at increasing concentrations of a drug (CONC 0-5) (CONC was increased sequentially at each timepoint, therefore this variable serves as both timepoint and concentration). I am treating CONC as a continuous variable here. I have chosen to have GRP as an explanatory variable/fixed effect as there are only 2 possible groups.
I have used the following command for a random slopes model:
Code:
xtmixed OUT i.GRP##c.CONC || id: CONC, mle variance
1 (red): the intercept of GRP0 at CONC 0
2 (green): the p-value for null hypothesis that there is no difference between GRP0 (the reference) and GRP1. This indicates the null hypothesis should be rejected: there is a difference. But is this just at baseline, or across all concentrations?
3 (blue): I am not sure here. Is it the p-value for the null hypothesis that there is no difference in OUT across all concentrations, but for both groups combined? And as it is <0.05, this suggests OUT does vary with CONC in some way?
4 (purple): p-value for the interaction - highly significant, suggesting there is an interaction and that OUT varies with CONC differently for each group
Thanks
Jem
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