Title: Doubly-Robust Nonparametric Estimation and Inference
Authors@R: person("David", "Benkeser", email = "benkeser@emory.edu", role = c("aut", "cre","cph"))
Description: Targeted minimum loss-based estimators of counterfactual means and causal effects that are doubly-robust with respect both to consistency and asymptotic normality (van der Laan (2014), <doi:10.1515/ijb-2012-0038>).
Imports: SuperLearner, plyr, np, foreach
Suggests: testthat, knitr, rmarkdown, gam, quadprog, nloptr, doParallel

person("Nima", "Hejazi", email = "nhejazi@berkeley.edu",
Description: Targeted minimum loss-based estimators of counterfactual means and
causal effects that are doubly-robust with respect both to consistency and
asymptotic normality (Benkeser et al (2017), <doi:10.1093/biomet/asx053>; MJ
Imports: SuperLearner, plyr, np, future, doFuture, future.batchtools
Suggests: testthat, knitr, rmarkdown, gam, quadprog, nloptr, parallel,

Imports: SuperLearner, plyr, np, future, doFuture, future.apply,
Suggests: testthat, knitr, rmarkdown, gam, earth, quadprog, nloptr,

Imports: SuperLearner, np, future, doFuture, future.apply,

Packaged: 2022-04-20 20:51:08 UTC; davidbenkeser

Title: Drug Interaction Modeling Based on Loewe Additivity Following
Author: Maxim Nazarov, Nele Goeyvaerts, Chris Harbron (original article and code)
Description: Perform assessment of synergy/antagonism for drug combinations based
on the Loewe additivity model, following Harbron's approach (Statistics in
Medicine, 2010, <doi:10.1002/sim.3916>). The package allows flexible modeling
of the drug interaction index and supports "2-stage" estimation in addition
to "1-stage" estimation, including bootstrap-based confidence intervals.
The method requires data on the monotherapy responses and the package
accommodates both checkerboard and ray designs. Functions are available for
graphical exploration of model goodness-of-fit and diagnostics, as well as
for synergy/antagonism assessment in 2D and 3D.
Imports: ggplot2, minpack.lm, BIGL (>= 0.9), rgl, nlme, Deriv, methods,
Suggests: knitr, rmarkdown, testthat, Cairo