randChecks-internal: Internal `randChecks` functions

Description

Internal randChecks functions

Usage

getBlockPerm(subclassIndicatorTable)
  permuteData.constrainedStandardizedCovMeanDiffs(X.matched, indicator.matched,
  threshold, X.full = NULL, indicator.full = NULL)
  permuteData.blocked.constrainedStandardizedCovMeanDiffs(X.matched, indicator.matched,
  subclass, threshold, X.full = NULL, indicator.full = NULL)
  permuteData.constrainedMD(X.matched, indicator.matched, threshold, X.full = NULL)
  permuteData.blocked.constrainedMD(X.matched, indicator.matched,
  subclass, threshold, X.full = NULL)
  getCompletePerms.balance(X.matched, indicator.matched,
  perms = 1000, X.full = NULL, indicator.full = NULL)
  getBlockPerms.balance(X.matched, indicator.matched,
  subclass, perms = 1000, X.full = NULL, indicator.full = NULL)
  getConstrainedDiffsPerms.balance(X.matched, indicator.matched,
  threshold, perms = 1000, X.full = NULL, indicator.full = NULL)
  getConstrainedDiffsBlockedPerms.balance(X.matched, indicator.matched,
  subclass, threshold, perms = 1000, X.full = NULL, indicator.full = NULL)
  getConstrainedMDPerms.balance(X.matched, indicator.matched,
  threshold, perms = 1000, X.full = NULL, indicator.full = NULL)
  getConstrainedMDBlockedPerms.balance(X.matched, indicator.matched,
  subclass, threshold, perms = 1000, X.full = NULL, indicator.full = NULL)
  getCompletePerms.md(X.matched, indicator.matched,
  perms = 1000, X.full = NULL)
  getBlockPerms.md(X.matched, indicator.matched,
  subclass, perms = 1000, X.full = NULL)
  getConstrainedDiffsPerms.md(X.matched, indicator.matched,
  threshold, perms = 1000, X.full = NULL, indicator.full = NULL)
  getConstrainedMDPerms.md(X.matched, indicator.matched,
  threshold, perms = 1000, X.full = NULL)
  getConstrainedDiffsBlockedPerms.md(X.matched, indicator.matched,
  subclass, threshold, perms = 1000,
  	X.full = NULL, indicator.full = NULL)
  getConstrainedMDBlockedPerms.md(X.matched, indicator.matched,
  subclass, threshold, perms = 1000, X.full = NULL)
  getAssignmentColor(assignment)

Arguments

Details

getBlockPerm is a helper function to permute an indicator within blocks (defined by a subclass).

permuteData.constrainedStandardizedCovMeanDiffs permutes an indicator given a constraint on standardized covariate mean differences.

permuteData.blocked.constrainedStandardizedCovMeanDiffs permutes an indicator within blocks given a constraint on standardized covariate mean differences.

permuteData.constrainedMD permutes an indicator given a constraint on the Mahalanobis distance.

permuteData.blocked.constrainedMD permutes an indicator within blocks given a constraint on the Mahalanobis distance.

getCompletePerms.balance returns standardized covariate mean differences across many permutations.

getBlockPerms.balance returns standardized covariate mean differences across many permutations within blocks.

getConstrainedDiffsPerms.balance returns standardized covariate mean differences across many permutations, conditional on a constraint on the standardized covariate mean differences.

getConstrainedDiffsBlockedPerms.balance returns standardized covariate mean differences across many permutations within blocks, conditional on a constraint on the standardized covariate mean differences.

getConstrainedMDPerms.balance returns standardized covariate mean differences across many permutations, conditional on a constraint on the Mahalanobis distance.

getConstrainedMDBlockedPerms.balance returns standardized covariate mean differences across many permutations within blcoks, conditional on a constraint on the Mahalanobis distance.

getCompletePerms.md returns the Mahalanobis distance across many permutations.

getBlockPerms.md returns the Mahalanobis distance across many permutations within blocks.

getConstrainedDiffsPerms.md returns the Mahalanobis distance across many permutations, conditional on a constraint on the standardized covariate mean differences.

getConstrainedMDPerms.md returns the Mahalanobis distance across many permutations, conditional on a constraint on the Mahalanobis distance.

getConstrainedDiffsBlockedPerms.md returns the Mahalanobis distance across many permutations within blocks, conditional on a constraint on the standardized covariate mean differences.

getConstrainedMDBlockedPerms.md returns the Mahalanobis distance across many permutations within blocks, conditional on a constraint on the Mahalanobis distance.

getAssignmentColor is a helper function that pairs different assignment mechanisms with different colors to be used in plots within randChecks.