Package index • verywise

All functions

as.mgh(): Create an object structured like an MGH object

barnard.rubin(): Pooled degrees of freedom calculation

build_supersubject(): Build "supersubject" by stacking all vertex data in one large file-backed matrix with dimensions n_subjects x n_vertices.

check_pheno_obj(): Check that object exists in the global environment

compute_clusters(): Compute significant clusters of vertices

estimate_fwhm(): Estimate full-width half maximum (FWHM)

fbm2mgh(): Save file backed matrix (FBM) to MGH file

fbm_col_has_0(): Check if all row elements are 0 in FBM

get_terms(): Unpack lme4 formula

hemi_vw_lmm(): Run vertex-wise linear mixed model in one hemisphere using lme4::lmer()

imp2list(): Convert imputation object to a list of dataframes

list.dirs.till(): List sub-directories till depth n

load.mgh(): Load an MGH file into memory

load_pheno_file(): Load "phenotype" file into R based on its extension

make_chunk_sequence(): Define chunks of vertices for analyses

mask_cortex(): Clean out vertices that are not on the cortex

pretty_message(): Print pretty messages to console

run_vw_lmm(): Run vertex-wise linear mixed model using lme4::lmer()

save.mgh(): Save an MGH file from memory

simulate_dataset(): Simulate a dataset including phenotype and FreeSurfer data

simulate_freesurfer_data(): Simulate FreeSurfer data

simulate_long_pheno_data(): Simulate phenotype data

single_lmm(): Run a single lme4::lmer model and extract stats

vw_message(): Print message to console if verbose = TRUE

vw_pool(): Pool lme4::lmer model output across imputed datasets