I have two soil treatments: CT and NT.
For each treatment, I have 11 CO2 measurements taken in 7 times, i.e. 11 "replicates" for 7 dates.
I'd like to evaluate if the measurements are different in time for the two treatments.
- replicates(11)=random factor;
- days=repeated measure factor (fixed factor)
- treatment = between subject factor (fixed factor)
- CO2 = Co2 emission measures (=dependent variable)
Is it correct to consider this as a nested two-level repeated measures ANOVA?
Is it correct to use the following R syntax?
m1 <- lmer(CO2~days*treatment+(days|replicates),mydata)
Is this a random intercept and slope model with replicates nested in treatment?
Is it correct to say that this model accounts for:
- the main effect of treatment and time and
- the interaction between the two?
What would be the difference between m1 and m2?
m2 <- lmer(CO2~days*treatment+(1|replicates),mydata)