adjust_TMTI: Adjust all p-values using a Closed Testing Procedeure and the...

In TMTI: 'Too Many, Too Improbable' (TMTI) Test Procedures

Adjust all p-values using a Closed Testing Procedeure and the TMTI family of tests.

Description

Adjust all p-values using a Closed Testing Procedeure and the TMTI family of tests.

Usage

adjust_TMTI(
  pvals,
  alpha = 0.05,
  B = 1000,
  gammaList = NULL,
  tau = NULL,
  K = NULL,
  is.sorted = FALSE,
  EarlyStop = FALSE,
  verbose = FALSE,
  mc.cores = 1L,
  chunksize = 4 * mc.cores,
  direction = "increasing",
  parallel.direction = "breadth",
  AdjustAll = FALSE,
  ...
)

Arguments

pvals	vector of p-values.
alpha	significance level. Defaults to 0.05.
B	Number of bootstrap replications. Only relevant if length(pvals) > 100 and no gammaList is supplied.
gammaList	A list of functions. These functions should be the CDFs of the chosen TMTI test for different m.
tau	Number between 0 and 1 or NULL, describing the truncation level.
K	Integer between >1 and m describing the truncation index.
is.sorted	Logical, indicating whether the supplied p-values are already sorted. Defaults to FALSE.
EarlyStop	Logical; set to TRUE to stop as soon as a hypothesis can be accepted at level alpha. This speeds up the procedure, but now only provides upper bounds on the adjusted p-values that are below alpha.
verbose	Logical; set to TRUE to print progress. Defaults to FALSE.
mc.cores	Number of cores to parallelize onto.
chunksize	Integer indicating the size of chunks to parallelize. E.g., if setting chunksize = mc.cores, each time a parallel computation is set up, each worker will perform only a single task. If mc.cores > chunksize, some threads will be inactive.
direction	String that is equal to either "increasing"/"i", "decreasing"/"d" or "binary"/"b". Determines the search direction. When set to"increasing", the function computes the exact adjusted p-value for all those hypotheses that can be rejected (while controlling the FWER), but is potentially slower than "decreasing". "decreasing"identifies all hypotheses that can be rejected with FWER control, but does not compute the actual adjusted p-values. "binary" performs a binary search for the number of hypotheses that can be rejected with FWER control. Defaults to "increasing". Note that 'binary' does not work with parallel.direction == 'breadth'.
parallel.direction	A string that is either "breadth" or "depth" (or abbreviated to "b" or "d), indicating in which direction to parallelize. Breadth-first parallelization uses a more efficient C++ implementation to adjust each p-value, but depth-first parallelization potentially finishes faster if using early stopping (EarlyStop = TRUE) and very few hypotheses can be rejected.
AdjustAll	Logical, indicating whether to adjust all p-values (TRUE) or only those that are marginally significant (FALSE). Defaults to FALSE.
...	Additional arguments.

Value

a data.frame containing adjusted p-values and their respective indices. If direction == 'decreasing' or 'binary', an integer describing the number of hypotheses that can be rejected with FWER control is returned.

Examples

p = sort(runif(100)) # Simulate and sort p-values
p[1:10] = p[1:10]**3 # Make the bottom 10 smaller, such that they correspond to false hypotheses
adjust_TMTI(p, alpha = 0.05, is.sorted = TRUE)

TMTI documentation built on Aug. 10, 2022, 5:06 p.m.