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iTOS (version 1.0.3)

Methods and Examples from Introduction to the Theory of Observational Studies

Description

Supplements for a book, "iTOS" = "Introduction to the Theory of Observational Studies." Data sets are 'aHDL' from Rosenbaum (2023a) and 'bingeM' from Rosenbaum (2023b) . The function makematch() uses two-criteria matching from Zhang et al. (2023) to create the matched data 'bingeM' from 'binge'. The makematch() function also implements optimal matching (Rosenbaum (1989) ) and matching with fine or near-fine balance (Rosenbaum et al. (2007) and Yang et al (2012) ). The book makes use of two other R packages, 'weightedRank' and 'tightenBlock'.

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Version

Install

install.packages('iTOS')

Monthly Downloads

189

Version

1.0.3

License

GPL-2

Maintainer

Paul Rosenbaum

Last Published

September 5th, 2024

Functions in iTOS (1.0.3)

Add a Near-exact Penalty to an Exisiting Distance Matrix.

Add an Integer Penalty to an Existing Distance Matrix

Add a Caliper to an Existing Cost Matrix

Compute expectations and variances for one stratum.

Convolution of Two Probability Generating Functions

Make the Network Used for Matching with Two Criteria

Rank-Based Mahalanobis Distance Matrix

Sensitivity Analysis Using Noether's Test for Matched Pairs

Alcohol and HDL Cholesterol

Cut a Covariate at Quantiles and Add a Penalty for Different Quantile Categories

Binge Drinking and High Blood Pressure -- Matched With Two Control Groups

Initialize a Distance Matrix.

Computes individual and pairwise treatment assignment probabilities.

Two-Criteria Matching

Amplification of sensitivity analysis in observational studies.

tools:::Rd_package_title("iTOS")

zeta function in sensitivity analysis

Binge Drinking and High Blood Pressure

Computes the null expectation and variance for one stratum.

Evaluate Covariate Balance in a Matched Sample