QUICKSTOP significance testing for partial correlation

This function will test whether the observed partial correlation is significant at a level of req_alpha, doing up to MaxIter permutations. Currently, it supports only grouping by discrete categories when calculating a partial correlation. Currenlty, only does two sided tests.

Usage

partialCorQUICKSTOP(
  pin_x,
  pin_y,
  pobsCor,
  pGroupFactor,
  pGroupSize,
  pnumGroup,
  pMaxIter,
  pn,
  preq_alpha,
  ptolerance_par,
  plog_decision_boundary,
  pseed
)

Arguments

pin_x

one of the two vectors to correlate.

pin_y

the other vector to calculate

pobsCor

the observed (partial) correlation between these varaiables

pGroupFactor

an integer vector labeling group membership, to correct for in the partial correlation. NEEDS TO BE ZERO BASED!

pGroupSize

an integer vector of size length(unique(pGroupFactor)), counting the number of members of each group (basically table(pGroupFactor)) as integer vector

pnumGroup

how many groups are there (len(pGroupSize))

pMaxIter

maximum number of iterations to do, as a REAL NUMBER

pn

length of x and y, as a REAL NUMBER

preq_alpha

the required alpha for significance

ptolerance_par

the tolerance region for quickstop. Suggested to be 1/100th of req_alpha'

plog_decision_boundary

log (base e) of 1/probability of incorrectly calling significance, as per quickstop paper (used to determine the log-odds)

pseed

A numeric vector of length 2, used to seed the internal xoroshiro128+ 1.0 random number generator. Note that currently, these values get modified per call, so pass in a copy if you wish to keep a seed for running same simulation twice

Value

a double vector of length 4, entry 1 is either 0, 1 (for TRUE/FALSE) or NA_REAL_ for significance determination NA_REAL_ is returned when the MaxIter were reached before a decision is made. Usually, this occurs when the real p value is close to, or falls within the tolerance region of (req_alpha, req_alpha+tolerance_par). Entry 2 is the current p value estimate. entry 3 is the total number of iterations performed. Entry 4 is the number of time a permuted value was larger in absolute value than the observed cor.