person("Clémence", "Leyrat", role = "ctb", email = "Clemence.Leyrat@lshtm.ac.uk"),
person("Elizabeth", "Stuart", role = "ctb", email = "EStuart@jhu.edu"))
Imports: broom, dplyr, graphics, methods, mice, stats, survey

Imports: MatchIt (>= 4.0.0), mice, rlang, survey, WeightIt
Suggests: Amelia, cobalt (>= 4.0.0), R.rsp

Description: Provides the necessary tools for the pre-processing techniques of matching and weighting multiply imputed datasets to control for effects of confounders and to reduce the degree of dependence on certain modeling assumptions in studying the causal associations between an exposure and an outcome. This package includes functions to perform matching within and across the multiply imputed datasets using several matching methods, to estimate weights of units in the imputed datasets using several weighting methods, to calculate the causal effect estimate in each matched or weighted dataset using parametric or non-parametric statistical models, and to pool the obtained estimates from these models according to Rubin's rules (please see <https://journal.r-project.org/archive/2021/RJ-2021-073/> for details).

Title: Multivariate and Propensity Score Matching with Balance
person("Jasjeet", "Singh Sekhon", role = c("aut","cre"), email = "jas.sekhon@yale.edu"),
person("Theo", "Saarinen", role = c("aut"), email = "theo_s@berkeley.edu")
Maintainer: Jasjeet Singh Sekhon <jas.sekhon@yale.edu>
Description: Provides functions for multivariate and propensity score matching
and for finding optimal balance based on a genetic search algorithm.
A variety of univariate and multivariate metrics to
determine if balance has been obtained are also provided. For
details, see the paper by Jasjeet Sekhon
Depends: R (>= 2.6.0), MASS (>= 7.2-1), graphics, grDevices, stats
Author: Jasjeet Singh Sekhon [aut, cre],

Suggests: parallel, rgenoud (>= 2.12), testthat

Title: Computation of the Balance - Sample Size Frontier in Matching
Author: Gary King, Christopher Lucas, and Richard Nielsen
Description: MatchingFrontier returns the subset of the data with the minimum imbalance for
every possible subset size (N - 1, N - 2, ...), down to the data set with the
minimum possible imbalance. The package also includes tools for the estimation
of causal effects for each subset size, as well as functions for visualization
Packaged: 2014-09-16 18:12:59 UTC; christopher