Build an explicit NIfTI source list for use with gds(..., format = "nifti").
If beta is provided without se, materialising the GDS creates a unit
variance placeholder with a warning. This supports raw beta/stat-map
workflows; the synthetic variance should not be interpreted as subject-level
uncertainty, and variance-weighted reducers will refuse such a GDS.
Usage
nifti_source(
beta = NULL,
se = NULL,
subject = NULL,
subjects = NULL,
contrast = NULL,
contrasts = NULL
)Arguments
- beta
Character vector of NIfTI paths or a directory containing beta/effect images (optional, can be
NULLif onlyseis provided)- se
Character vector of NIfTI paths or a directory containing standard error images (optional, can be
NULLif onlybetais provided)- subject, subjects
Optional subject labels. When both
betaandseare supplied, these labels declare that the vectors are already aligned in matching subject order and bypass filename-key pairing.- contrast, contrasts
Optional contrast labels. Length must match the number of contrasts in each NIfTI image (one for ordinary 3D maps).
Details
When both beta and se are supplied, files are paired by subject key unless
explicit subject/subjects labels are supplied. The fallback key is the file
basename (extension removed) with a trailing statistic token stripped,
matching ([_.-](beta|cope|varcope|var|variance|effect|se|stderr|sterr|sigma|std(err)?))+$
(case insensitive). For example sub-01_beta.nii.gz and sub-01_se.nii.gz
both reduce to the key sub-01. Filenames where the statistic token is not
last (e.g. sub-01_stat-beta_sm-2.nii.gz) will fail to pair unless explicit
subject labels are provided. For beta/stat-only maps, prefer
gds_from_scalar_maps(), which takes an explicit subject vector and avoids
filename heuristics entirely.