[R] 3 x 2 mixed factorial design - which model is correct
Katerina Pappa (PGR)
@@p@pp@@1 @end|ng |rom re@e@rch@g|@@@c@uk
Tue Feb 9 13:52:28 CET 2021
Hello everyone,
I was hoping you could help with a few R-related questions.
I have a 3 x 2 mixed factorial design. This is a longitudinal design, where two groups of participants were assessed over three time points.
Factor Time has 3 levels (time 1, 2 and 3)
Factor Group has 2 levels (groups 1 and 2)
Dependent variables are continuous and represent gray matter volumes for 6 regions of interest
I have arranged the data as indicated below:
A tibble: 111 x 13
## ID Age Time Group lCau rCau lHip rHip lPut rPut T2vT1 T3vT1 G
## <fct> <dbl> <fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 BT02 22 T1-P� G2 2.65 2.71 2.58 2.83 3.17 3.05 -0.333 -0.333 -0.5
## 2 BT02 22 T2-E� G2 2.69 2.76 2.62 2.90 2.95 3.09 0.667 -0.333 -0.5
## 3 BT02 22 T3-P� G2 2.66 2.72 2.56 2.87 2.99 2.96 -0.333 0.667 -0.5
## 4 BT03 22 T1-P� G1 2.20 2.37 2.46 2.81 3.51 3.45 -0.333 -0.333 0.5
## 5 BT03 22 T2-E� G1 2.18 2.38 2.47 2.77 3.38 3.48 0.667 -0.333 0.5
## 6 BT03 22 T3-P� G1 2.18 2.33 2.44 2.78 3.61 3.66 -0.333 0.667 0.5
## 7 BT04 19 T1-P� G2 2.93 3.10 2.89 3.19 3.57 3.70 -0.333 -0.333 -0.5
## 8 BT04 19 T2-E� G2 2.91 3.07 2.86 3.18 3.46 3.60 0.667 -0.333 -0.5
## 9 BT04 19 T3-P� G2 2.84 3.01 2.90 3.23 3.54 3.71 -0.333 0.667 -0.5
taking the left caudate, .i.e. lCau, as an example:
Q1: Anova model
aov (lCau ~ Time*Group + Error(ID)) �> is this model correct?
Q2: lm model
And then i used dummy coding for the lm model
lmer(lCau ~ (T2vT1 + T3vT1)*G+ (1 |ID)) �> is this model correct?
Are these models correct for this type of data?
Q3: any thoughts on how to deal with unbalanced design (I have missing data for one participant for Time2)
Thank you!
Katerina
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