Note: Uses exact standard errors when covariance is available (return_cov="tri") or for ROI CSV fits with non-robust estimation; otherwise uses a diagonal variance approximation.
Usage
# S3 method for class 'fmri_meta'
contrast(x, contrast, ...)
Examples
toy_meta <- structure(
list(
coefficients = matrix(c(0.3, 0.1), nrow = 1,
dimnames = list(NULL, c("A", "B"))),
se = matrix(c(0.05, 0.06), nrow = 1),
robust = "none"
),
class = "fmri_meta"
)
contrast(toy_meta, c(1, -1))
#> $estimate
#> [1] 0.2
#>
#> $se
#> [1] 0.0781025
#>
#> $z
#> [1] 2.560738
#>
#> $p
#> [,1]
#> [1,] 0.01044502
#>
#> $weights
#> [1] 1 -1
#>
#> $name
#> [1] "custom"
#>
#> $parent
#> fMRI Meta-Analysis Results
#> ==========================
#>
#> Method:
#> Robust: none
#> Formula: NULL
#> Subjects:
#>
#> attr(,"class")
#> [1] "fmri_meta_contrast"