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Fit a Robust Linear Model for fMRI Data Analysis

Source: R/fmrirlm.R
fmri_rlm.Rd

This function fits a robust linear regression model for fMRI data analysis using the specified model formula, block structure, and dataset. The model can be fit using either a runwise or chunkwise data splitting strategy.

Usage

fmri_rlm(
  formula,
  block,
  baseline_model = NULL,
  dataset,
  durations = 0,
  drop_empty = TRUE,
  strategy = c("runwise", "chunkwise"),
  nchunks = 10,
  cor_struct = c("iid", "ar1", "ar2", "arp"),
  cor_iter = 1L,
  cor_global = FALSE,
  ar_p = NULL,
  ar1_exact_first = FALSE,
  robust_psi = c("huber", "bisquare"),
  robust_k_huber = 1.345,
  robust_c_tukey = 4.685,
  robust_max_iter = 2L,
  robust_scale_scope = c("run", "global"),
  ...
)

Arguments

formula

A model formula describing the event structure or an fmri_model object.

block

The model formula for block structure.

baseline_model

(Optional) A baseline_model object. Default is NULL.

dataset

An fmri_dataset object containing the time-series data.

durations

A vector of event durations. Default is 0.

drop_empty

Logical. Whether to remove factor levels with zero size. Default is TRUE.

strategy

The data splitting strategy, either "runwise" or "chunkwise". Default is "runwise".

nchunks

Number of data chunks when strategy is "chunkwise". Default is 10.

cor_struct

Correlation structure: "iid", "ar1", "ar2", or "arp". Default is "iid".

cor_iter

Number of iterations for AR parameter estimation. Default is 1.

cor_global

Whether to use global AR parameters. Default is FALSE.

ar_p

Order of autoregressive model for "arp" structure. Default is NULL.

ar1_exact_first

Whether to use exact AR(1) for first iteration. Default is FALSE.

robust_psi

Robust psi function: "huber" or "bisquare". Default is "huber".

robust_k_huber

Tuning constant for Huber's psi. Default is 1.345.

robust_c_tukey

Tuning constant for Tukey's bisquare. Default is 4.685.

robust_max_iter

Maximum iterations for robust fitting. Default is 2.

robust_scale_scope

Scope for robust scale estimation: "run" or "global". Default is "run".

...

Additional arguments passed to fmri_lm

Value

A fitted robust linear regression model for fMRI data analysis.

Examples

etab <- data.frame(onset=c(1,30,15,25), fac=factor(c("A", "B", "A", "B")), run=c(1,1,2,2))
etab2 <- data.frame(onset=c(1,30,65,75), fac=factor(c("A", "B", "A", "B")), run=c(1,1,1,1))
mat <- matrix(rnorm(100*100), 100,100)
dset <- fmridataset::matrix_dataset(mat, TR=1, run_length=c(50,50),event_table=etab)
dset2 <- fmridataset::matrix_dataset(mat, TR=1, run_length=c(100),event_table=etab2)
lm.1 <- fmri_rlm(onset ~ hrf(fac), block= ~ run, dataset=dset)
lm.2 <- fmri_rlm(onset ~ hrf(fac), block= ~ run, dataset=dset2)