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Simulate a complete longitudinal brain surface dataset

Source: R/simulate_longit_dataset.R
simulate_longit_dataset.Rd

High-level wrapper that:

  1. Generates a longitudinal phenotype data.frame via simulate_long_pheno_data();

  2. Writes it to path/phenotype.csv;

  3. Calls simulate_freesurfer_data() for each requested hemisphere.

Usage

simulate_longit_dataset(
  path,
  data_structure = list(cohort1 = list(sessions = c("01", "02", "03"), n_subjects = 100),
    cohort2 = list(sessions = c("01", "02"), n_subjects = 150)),
  baseline = list(age = c(mean = 10, sd = 0.5), sex = c(levels = c("Male", "Female")),
    wisdom = c(mean = 0, sd = 1)),
  change = list(age = c(mean = 4, sd = 0.5), wisdom = c(mean = 1, sd = 0.5)),
  roi_associations = list(temporalpole = c(age = 1.3, sex = 0.5), entorhinal = c(age =
    0.9), frontalpole = c(wisdom = 0.7)),
  simulate_other_rois = FALSE,
  only_save_ss_matrix = FALSE,
  hemi = "both",
  measure = "thickness",
  vw_mean = 2.5,
  vw_sd = 0.5,
  subj_sd = 0.2,
  site_sd = 0.1,
  fs_template = "fsaverage",
  fwhmc = "fwhm10",
  seed = 3108,
  verbose = TRUE
)

Arguments

path

Character string; root directory in which to write .mgh files. Created if it does not exist.

data_structure

Named list specifying site/cohort structure. Each element must be a list with:

sessions

Character vector of unique session labels.

n_subjects

Positive integer, number of subjects.

baseline

Named list defining baseline distributions. Supports continuous covariates (c(mean, sd)) and categorical covariates (c(levels = ...)). See section Supported covariates.

change

Named list of c(mean, sd) specifying the per-wave mean shift and noise SD for longitudinal covariates. Only continuous variables should appear here.

roi_associations

Named list of named numeric vectors. Names of the list are Desikan-Killiany ROI labels; names of each vector are column names in pheno; values are beta coefficients. Example: list(temporalpole = c(age = 0.3, wisdom = 0.5)).

simulate_other_rois

Logical; if TRUE all non-association ROIs are simulated under the null.

only_save_ss_matrix

only save the supersubject matrix

hemi

One of "lh", "rh", or "both" (default: "both").

measure

Character; FreeSurfer surface measure, e.g. "thickness" or "area".

vw_mean

Numeric; mean of the vertex-level residual noise (i.e. grand-mean cortical thickness).

vw_sd

Numeric \(\geq 0\); SD of vertex-level residual noise.

subj_sd

Numeric \(\geq 0\); SD of the subject random intercept.

site_sd

Numeric \(\geq 0\); SD of the site random intercept. Ignored when there is only one site (intercept drawn as a single value).

fs_template

Character; FreeSurfer template space, e.g. "fsaverage".

fwhmc

Character; smoothing kernel label, e.g. "fwhm10".

seed

Integer random seed for reproducibility.

verbose

Logical

Value

NULL invisibly. Side effects: phenotype.csv and vertex-wise .mgh files written under path.

See also

simulate_long_pheno_data(), simulate_freesurfer_data()

Examples

if (FALSE) { # dir.exists("path/to/simulated/dataset")
simulate_longit_dataset(
  path = 'path/to/simulated/dataset/',
  data_structure = list(
    GENR = list(sessions = c("01", "02", "03"), n_subjects = 50)
  ),
  roi_associations = list(temporalpole = c(age = 1.3)),
  hemi = "lh"
)
}