Hi AFNI Crew,
I am attempting to use 3dLME to test if an interaction between symptom severity and age predict our brain measure in a longitudinal sample (scan 1 and follow-up scan 2). Our design is purely within-subjects (aside from a 'sex' nuisance covariate) with a model and data table similar to the following:
-model "SYMP_SEV*AGE + SEX + COV"
-ranEff "~1"
subj SYMP_SEV AGE SEX COV InputFile
_019 0.907720004 12.66 F 1377.5 ${data}/019_SCAN1 \
_019 1.176118983 15.23 F 1328.14 ${data}/019_SCAN2 \
_020 -0.925335639 15.68 M 1560.22 ${data}/020_SCAN1 \
_020 -1.147441677 14.63 M 1567.69 ${data}/020_SCAN2 \
_021 -1.316514248 11.04 F 1467.67 ${data}/021_SCAN1 \
_021 -0.740970281 12.09 F 1452.89 ${data}/021_SCAN2 \
.....
_118 0.627853985 17.68 M 1804.6 ${data}/118_SCAN1 \
_118 -0.474358615 18.77 M 1833.68 ${data}/118_SCAN2 \
_122 0.78376315 14.24 F 1364.45 ${data}/122_SCAN1 \
_122 0.107800324 15.37 F 1385.81 ${data}/122_SCAN2
1) Should we include a 'scan number' variable? Originally we thought this variable would be redundant, as this was a naturalistic follow-up and the only difference between our 'pre' and 'post' measures is the passage of time (which we assume is captured by the difference in 'AGE' between scan1 and scan2). However, we are unsure how the model is aware that each measure is within-subject and varies between scan1 and scan2.
2) Would we also model SUBJ (as well as -ranEFF "~1 + SUBJ") to indicate all continuous repeated measures within SUBJ?
Thanks for your help!
Taylor
