GPA -> Difference -> Regression/PCA Take the difference after GPA and before data reduction or non-parametric testing. E.g.,
Cevidanes, Lucia H. S., Alexandre A. Franco, Guido Gerig, William R. Proffit, Dennis E. Slice, Donald H. Enlow, Helio K. Yamashita, Yong-Jik Kim, Marco A. Scanavini, and Julio W. Vigorito. “Assessment of Mandibular Growth and Response to Orthopedic Treatment with 3-Dimensional Magnetic Resonance Images.” *American Journal of Orthodontics and Dentofacial Orthopedics* 128, no. 1 (July 1, 2005): 16–26. doi:10.1016/j.ajodo.2004.03.032. -ds On Wednesday, August 19, 2015 at 8:48:42 AM UTC-4, lv xiao wrote: > > 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 > -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org To unsubscribe from this group and stop receiving emails from it, send an email to morphmet+unsubscr...@morphometrics.org.