Dear all,
*My example:*
I have 150 participants in my sample. At time point 1 (eg., at birth), I
collected some background information (including both categorical and
continuous variables) from the participants. Images of the participants
were taken at time point 2 (eg., 6 months) and time point 3 (eg., 12
months).
*My aim:*
I wish to investigate whether those background information collected at
birth predict participants' shape changes from 6 to 12 months.
*Proposed methods:*
Perform between-group PCA (BGPCA) in steps below:
Step 1: Group the shape data by time point. One group for 6 months data,
and the other for 12 months data;
Step 2: Perform BGPCA (in PCAGen8) and extract the most significant
principal components (PCs) from scree plot;
Step 3: Extract the PC scores ("Save PCA Scores" button in PCAGen8)
Step 4: Since each participant appeared in both groups, I can calculate the
difference of each participant's PC scores between the two groups (time
points) for each extracted PC;
Step 5: Each participant is then associated with one score reflecting
his/her shape change along a particular PC (eg., PC 1). This score is then
used as the dependent variable so that conventional
statistical analyses such as simple linear regression and ANOVA, can be
performed.
*My question:*
Q 1: Is the steps above appropriate?
Q 2: Since the same participants are in both groups (groups differ only in
the chronological order the shapes were measured), the two groups are
correlated instead of being independent. Will such
correlation affect the correctness of BGPCA in this example. Is there any
way out if correlation is indeed a problem?
Thank you very much!
Best regards,
Patrick
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