Hi,
I have the following dataset:
two groups of samples, TOP (9) and BOTTOM (10), which I have classified with the dummy variable GRP, 0 and 1 respectively. I have performed experiments on these samples to measure the outcome/dependent variable OUT, measuring this at baseline, and then at 6 further timepoints (CONC, for concentration) where a drug concentration was increased incrementally at each timepoint.
I am interested to know the following:
i. is there a difference overall between groups TOP and BOTTOM? (as these are the only possible groups for an individual sample to belong to, I assume GRP is an explanatory variable rather than a level... So level 1 is the repeated measures, and level 2 is the individual sample.
ii. is there a difference in either group in the outcome variable with increasing concentration of the drug? i.e. is there a significant increase/decrease in OUT with increasing CONC (drug concentration)?
I have done quite a bit of reading, and as far as I can see, I would begin with something like
xtmixed OUT CONC
What I am not sure about is:
i. the precise order of the next steps - do I need to build the command layer by layer, e.g. first add random intercept, then random slope, then add GRP as a fixed explanatory variable?
ii. how to test the significance of the differences I am interested in (above)
iii. how to generate mean predicted values for each group (TOP and BOTTOM) at each drug concentration (CONC) so I can plot the two predicted group lines
Any help would be gratefully received.
Jem
I have the following dataset:
two groups of samples, TOP (9) and BOTTOM (10), which I have classified with the dummy variable GRP, 0 and 1 respectively. I have performed experiments on these samples to measure the outcome/dependent variable OUT, measuring this at baseline, and then at 6 further timepoints (CONC, for concentration) where a drug concentration was increased incrementally at each timepoint.
I am interested to know the following:
i. is there a difference overall between groups TOP and BOTTOM? (as these are the only possible groups for an individual sample to belong to, I assume GRP is an explanatory variable rather than a level... So level 1 is the repeated measures, and level 2 is the individual sample.
ii. is there a difference in either group in the outcome variable with increasing concentration of the drug? i.e. is there a significant increase/decrease in OUT with increasing CONC (drug concentration)?
I have done quite a bit of reading, and as far as I can see, I would begin with something like
xtmixed OUT CONC
What I am not sure about is:
i. the precise order of the next steps - do I need to build the command layer by layer, e.g. first add random intercept, then random slope, then add GRP as a fixed explanatory variable?
ii. how to test the significance of the differences I am interested in (above)
iii. how to generate mean predicted values for each group (TOP and BOTTOM) at each drug concentration (CONC) so I can plot the two predicted group lines
Any help would be gratefully received.
Jem
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