iTOS-package {iTOS} | R Documentation |
Supplements for a book, "iTOS" = "Introduction to the Theory of Observational Studies." Data sets are 'aHDL' from Rosenbaum (2023a) <doi:10.1111/biom.13558> and 'bingeM' from Rosenbaum (2023b) <doi:10.1111/biom.13921>. The function makematch() uses two-criteria matching from Zhang et al. (2023) <doi:10.1080/01621459.2021.1981337> to create the matched data 'bingeM' from 'binge'. The makematch() function also implements optimal matching (Rosenbaum (1989) <doi:10.2307/2290079>) and matching with fine or near-fine balance (Rosenbaum et al. (2007) <doi:10.1198/016214506000001059> and Yang et al (2012) <doi:10.1111/j.1541-0420.2011.01691.x>). The book makes use of two other R packages, 'weightedRank' and 'tightenBlock'.
The DESCRIPTION file:
Package: | iTOS |
Type: | Package |
Title: | Methods and Examples from Introduction to the Theory of Observational Studies |
Version: | 1.0.3 |
Authors@R: | person(given = c("Paul", "R."), family = "Rosenbaum", role = c("aut", "cre"), email = "rosenbaum@wharton.upenn.edu") |
Author: | Paul R. Rosenbaum [aut, cre] |
Maintainer: | Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu> |
Description: | Supplements for a book, "iTOS" = "Introduction to the Theory of Observational Studies." Data sets are 'aHDL' from Rosenbaum (2023a) <doi:10.1111/biom.13558> and 'bingeM' from Rosenbaum (2023b) <doi:10.1111/biom.13921>. The function makematch() uses two-criteria matching from Zhang et al. (2023) <doi:10.1080/01621459.2021.1981337> to create the matched data 'bingeM' from 'binge'. The makematch() function also implements optimal matching (Rosenbaum (1989) <doi:10.2307/2290079>) and matching with fine or near-fine balance (Rosenbaum et al. (2007) <doi:10.1198/016214506000001059> and Yang et al (2012) <doi:10.1111/j.1541-0420.2011.01691.x>). The book makes use of two other R packages, 'weightedRank' and 'tightenBlock'. |
License: | GPL-2 |
Encoding: | UTF-8 |
LazyData: | true |
Imports: | stats, MASS, rcbalance, BiasedUrn, xtable |
Suggests: | weightedRank |
Depends: | R (>= 3.5.0) |
Index of help topics:
aHDL Alcohol and HDL Cholesterol addMahal Rank-Based Mahalanobis Distance Matrix addNearExact Add a Near-exact Penalty to an Exisiting Distance Matrix. addcaliper Add a Caliper to an Existing Cost Matrix addinteger Add an Integer Penalty to an Existing Distance Matrix addquantile Cut a Covariate at Quantiles and Add a Penalty for Different Quantile Categories amplify Amplification of sensitivity analysis in observational studies. binge Binge Drinking and High Blood Pressure bingeM Binge Drinking and High Blood Pressure - Matched With Two Control Groups computep Computes individual and pairwise treatment assignment probabilities. ev Computes the null expectation and variance for one stratum. evalBal Evaluate Covariate Balance in a Matched Sample evall Compute expectations and variances for one stratum. gconv Convolution of Two Probability Generating Functions iTOS-package Methods and Examples from Introduction to the Theory of Observational Studies makematch Two-Criteria Matching makenetwork Make the Network Used for Matching with Two Criteria noether Sensitivity Analysis Using Noether's Test for Matched Pairs startcost Initialize a Distance Matrix. zeta zeta function in sensitivity analysis
Paul R. Rosenbaum [aut, cre]
Maintainer: Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu>
Rosenbaum, Paul R. Introduction to the Theory of Observational Studies. Manuscript, 2024.
Rosenbaum, P. R. (1989) <doi:10.2307/2290079> Optimal matching for observational studies. Journal of the American Statistical Association, 84, 1024-1032.
Rosenbaum, Paul R., Richard N. Ross, and Jeffrey H. Silber (2007) <doi:10.1198/016214506000001059> Minimum distance matched sampling with fine balance in an observational study of treatment for ovarian cancer. Journal of the American Statistical Association 102, 75-83.
Rosenbaum, P. R. (2023a) <doi:10.1111/biom.13558> Sensitivity analyses informed by tests for bias in observational studies. Biometrics 79, 475-487.
Rosenbaum, P. R. (2023b) <doi:10.1111/biom.13921> A second evidence factor for a second control group. Biometrics, 79, 3968-3980.
Yang, D., Small, D. S., Silber, J. H. and Rosenbaum, P. R. (2012) <doi:10.1111/j.1541-0420.2011.01691.x> Optimal matching with minimal deviation from fine balance in a study of obesity and surgical outcomes. Biometrics, 68, 628-636.
Zhang, B., D. S. Small, K. B. Lasater, M. McHugh, J. H. Silber, and P. R. Rosenbaum (2023) <doi:10.1080/01621459.2021.1981337> Matching one sample according to two criteria in observational studies. Journal of the American Statistical Association, 118, 1140-1151.
data(binge)
table(binge$AlcGroup)
data(aHDL)
table(aHDL$grp)