Extract Standard Errors from a Model Fit

Extract standard errors of parameter estimates from a fitted model object. This is part of a family of functions for extracting statistical measures.

Usage

standard_error(x, ...)

# S3 method for class 'fmri_latent_lm'
standard_error(x, type = c("betas", "contrasts"), recon = FALSE, ...)

# S3 method for class 'fmri_lm'
standard_error(x, type = c("betas", "contrasts"), ...)

Arguments

x

The fitted model object

...

Additional arguments passed to methods

type

For fmri_lm fits, the parameter family: "betas" (default) for the event coefficients returned by coef(), or "contrasts". "estimates" is accepted as a synonym of "betas".

recon

Logical; whether to reconstruct the full matrix representation (default: FALSE)

Value

A tibble or matrix containing standard errors of parameter estimates. For fmri_lm fits, one row per voxel and one column per term, in the same orientation as coef().

See also

Other statistical_measures: coef_names(), p_values(), stats()

Examples

# Create example data
event_data <- data.frame(
  condition = factor(c("A", "B", "A", "B")),
  onsets = c(1, 10, 20, 30),
  run = c(1, 1, 1, 1)
)

# Create sampling frame and dataset
sframe <- sampling_frame(blocklens = 50, TR = 2)
dset <- matrix_frame(
  matrix(rnorm(50 * 2), 50, 2),
  TR = 2,
  run_length = 50,
  event_table = event_data
)

# Fit model
fit <- fmri_lm(
  onsets ~ hrf(condition),
  block = ~run,
  dataset = dset
)

# Extract standard errors
se <- standard_error(fit)