4. Three habitat designs
Background. A habitat design decides which rows are clustered and whether one model is shared by the whole cohort or fitted per subject. Purpose. Run the same data through each design and see what changes: shared vs. per-subject habitat ids, supervoxels vs. voxels.
The complete analysis is two-step: partition, then pool, then
fit. These pages change that stage list and nothing else.
Design |
|
|
|
|---|---|---|---|
two-step |
yes |
yes |
supervoxels, cohort |
inside each subject |
no |
no |
voxels, one subject |
pooling voxels |
no |
yes |
voxels, cohort |
two_step_habitat, one_step_habitat and direct_pooling_habitat
build those lists. Habitat ids match across subjects only when fit
ran once on the cohort. Otherwise match labels first
(6. Matching Habitat Labels).
Two steps — Defining habitats in two steps.
Inside each subject — Defining habitats inside each subject.
Pooling voxels — Pooling voxels across the cohort.
Applying a saved model is the next section. Opening each stage is 2. Each stage.
