multiresponse_bootstrap_lm: Multiresponse Bootstrap Linear Model

In bbuchsbaum/fmrireg: R package for the anlysis of fmri data

Multiresponse Bootstrap Linear Model

Description

Performs block bootstrap resampling for multiresponse linear models, particularly useful for fMRI time series data where temporal dependencies exist. The function implements a block bootstrap approach to maintain the temporal correlation structure within the data.

Usage

multiresponse_bootstrap_lm(
  form,
  data_env,
  conlist,
  vnames,
  fcon,
  modmat = NULL,
  block_size = 30,
  boot_rows = FALSE,
  nboot = 100,
  event_indices
)

Arguments

form	Formula for the linear model. Required if modmat is NULL.
data_env	Environment containing the data for the linear model.
conlist	List of contrasts to be computed for each bootstrap sample.
vnames	Vector of variable names.
fcon	Contrasts for fixed effects.
modmat	Optional pre-computed model matrix. If provided, form is ignored.
block_size	Size of the blocks for the bootstrap (default: 30). Should be large enough to capture temporal dependencies but small enough to allow sufficient randomization.
boot_rows	Logical flag indicating whether to bootstrap rows (default: FALSE).
nboot	Number of bootstrap iterations (default: 100).
event_indices	Indices of events for computing beta covariances.

Details

The function performs the following steps:

1. Fits the original linear model

2. Implements block bootstrap resampling of residuals

3. Reconstructs response variables using fitted values and resampled residuals

4. Computes contrasts for each bootstrap sample

The block bootstrap approach helps preserve temporal dependencies in the data by resampling blocks of consecutive observations rather than individual observations.

Value

A list containing:

• original: The fitted original model with contrasts

• con_cov: Covariance matrices for contrasts (if contrasts provided)

• beta_cov: Covariance matrices for beta estimates

• nboot: Number of bootstrap iterations performed

• bootstrap: Logical indicating this is a bootstrap result

Examples

## Not run: 
# Simple example with synthetic data
X <- model.matrix(~ x1 + x2, data = data.frame(x1 = rnorm(100), x2 = rnorm(100)))
y <- matrix(rnorm(100 * 3), 100, 3)  # 3 response variables
result <- multiresponse_bootstrap_lm(modmat = X, data_env = list(.y = y),
                                    nboot = 100, block_size = 20)

## End(Not run)

bbuchsbaum/fmrireg documentation built on March 1, 2025, 11:20 a.m.