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sensitivityIxJ (version 0.1.5)

Exact Nonparametric Sensitivity Analysis for I by J Contingency Tables

Description

Implements exact, normally approximated, and sampling-based sensitivity analysis for observational studies with contingency tables. Includes exact (kernel-based), normal approximation, and sequential importance sampling (SIS) methods using 'Rcpp' for computational efficiency. The methods build upon the framework introduced in Rosenbaum (2002) and the generalized design sensitivity framework developed by Chiu (2025) .

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Version

Install

install.packages('sensitivityIxJ')

Monthly Downloads

124

Version

0.1.5

License

GPL-3

Maintainer

Elaine Chiu

Last Published

October 16th, 2025

Functions in sensitivityIxJ (0.1.5)

estimate_tables

Estimate the Total Number of Tables
norm.score.sen.IxJ

Normal Approximation Sensitivity Analysis for I by J Tables
exact.score.sen.IxJ

Exact Sensitivity Analysis for Sum Score (Ordinal) Tests in I by J Tables
generic.I.by.J.sensitivity.point.probability

Compute the exact Probability of a Single Table for the Generic Bias Model
norm_single_u_allocation_p_value

Compute the normal-approximation-based z-score and p-value for a given 2 by 2, 2 by 3, 2 by 4, 2 by 5, 3 by 2, 4 by 2, or 3 by 3 contingency table.
sampling.score.sen.IxJ

Monte Carlo Score Test Sensitivity Analysis for I by J Tables
exact.general.sen.IxJ

Exact Sensitivity Analysis for General Test Statistics in I by J Tables
possible.table

Generate All Possible Contingency Tables Exceeding or Not Exceeding a Threshold
sampling.general.sen.IxJ

Monte Carlo Sensitivity Analysis for General Permutation-Invariant Test Statistics in I by J Tables