Fit a Linear Regression Model for fMRI Data Analysis

fmri_lm is a generic for fitting fMRI regression models. The default interface accepts a model formula and dataset. An alternative method can be used with a preconstructed fmri_model object that already contains the design and data.

The public fitting boundary separates statistical choices in fmri_lm_control() from mechanical execution choices in compute_spec(). Optional engines use the same control object and receive their private arguments through engine_args.

Usage

fmri_lm(formula, ...)

# S3 method for class 'formula'
fmri_lm(
  formula,
  block,
  baseline_model = NULL,
  dataset,
  durations = 0,
  drop_empty = TRUE,
  control = fmri_lm_control(estimation = estimation_spec("runwise_meta")),
  compute = compute_spec(),
  engine = NULL,
  engine_args = list(),
  lowrank = NULL,
  ...
)

# S3 method for class 'fmri_model'
fmri_lm(
  formula,
  dataset = NULL,
  control = fmri_lm_control(estimation = estimation_spec("runwise_meta")),
  compute = compute_spec(),
  engine = NULL,
  engine_args = list(),
  lowrank = NULL,
  ...
)

Arguments

formula: A model formula describing the event structure or an fmri_model object.
...: Transitional legacy arguments retained for one compatibility window. New code must express statistical choices in control and execution choices in compute; unknown arguments are rejected.
block: Formula describing run/block structure.
baseline_model: Optional baseline/nuisance model.
dataset: An fmri_dataset. For an fmri_model method this may be omitted when the model already owns its dataset.
durations: Event durations passed to model construction.
drop_empty: Remove empty factor levels during model construction.
control: A validated fmri_lm_control().
compute: A validated compute_spec().
engine: Optional registered engine name.
engine_args: Named list passed only to engine.
lowrank: Optional lowrank_control() for the latent-sketch engine.

Value

An object of class fmri_lm.