Permutation Test for Fixed Effects in FMM

Tests significance of fixed effects (covariates) using a permutation-based F-test that respects the within-subject correlation.

Usage

fmm.test.fixed(
  fdataobj,
  subject.ids,
  covariates,
  ncomp = 3,
  n.perm = 1000,
  seed = NULL
)

Arguments

fdataobj

An object of class 'fdata'.

subject.ids

Integer vector of subject identifiers.

covariates

Matrix of covariates (n_total x p).

ncomp

Number of FPC components (default 3).

n.perm

Number of permutations (default 1000).

seed

Random seed.

Value

An object of class 'fmm.test' with components:

f.statistics

F-statistic per covariate

p.values

P-values per covariate

Examples

# \donttest{
fd <- fdata(matrix(rnorm(500), 50, 10), argvals = seq(0, 1, length.out = 10))
subject <- rep(1:10, each = 5)
x <- cbind(rnorm(50))
test <- fmm.test.fixed(fd, subject.ids = subject, covariates = x,
                        n.perm = 100)
test
#> Fixed Effects Permutation Test
#> ==============================
#>   Permutations: 100 
#> 
#>             F.statistic P.value
#> Covariate 1      0.0029 0.74257
# }