ivmodel-bransonKeele-internal: Internal 'ivmodel' functions for Branson and Keele (2020)

In ivmodel: Statistical Inference and Sensitivity Analysis for Instrumental Variables Model

Internal ivmodel functions for Branson and Keele (2020)

Description

Internal ivmodel functions for Branson and Keele (2020)

Usage

	permuteData.biasedCoin(N, probs)
	getBlockPerm(subclassIndicatorTable)
	getCompletePerms.meanDiffs(X, indicator, perms = 1000)
	getCompletePerms.balance(X, indicator, perms = 1000)
	getCompletePerms.md(X, indicator, perms = 1000)
	getCompletePerms.absBias(X, D = NULL, Z = NULL, perms = 1000)
	getBlockPerms.md(X, indicator, subclass, perms = 1000)
	getBlockPerms.absBias(X, D = NULL, Z = NULL, subclass = NULL, perms = 1000)
	getBernoulliPerms.md(X, indicator, perms = 1000)
	getBernoulliPerms.absBias(X, D = NULL, Z = NULL, perms = 1000)

Details

permuteData.biasedCoin permutes the treatment indicator according to biased-coin randomization (i.e., Bernoulli trials). getBlockPerm permutes an indicator (instrument or exposure) within a subclass. getCompletePerms.meanDiffs returns the covariate mean differences across many permutations of an indicator. getCompletePerms.balance returns the standardized covariate mean differences across many permutations of an indicator. getCompletePerms.md returns the Mahalanobis distance across many permutations of an indicator. getCompletePerms.absBias returns the sum of absolute biases across many permutations of an indicator. getBlockPerms.md returns the Mahalanobis distance across many block permutations of an indicator. getBlockPerms.absBias returns the sum of absolute biases across many block permutations of an indicator. getBernoulliPerms.md returns the Mahalanobis distance across many Bernoulli-trial permutations of an indicator. getBernoulliPerms.absBias returns the sum of absolute biases across many Bernoulli-trial permutations of an indicator.

Author(s)

Zach Branson and Luke Keele

ivmodel documentation built on April 9, 2023, 5:08 p.m.