testthat, dplyr, tidyr, lubridate, SharpeR, sandwich,
formatR, knitr
'AllClass.r' 'utils.r' 'Ops.r' 'bind.r' 'blockrep.r'
'coerce.r' 'data.r' 'det.r' 'diag.r' 'eigen.r' 'elwise.r'
'madness_pkg.r' 'matwise.r' 'max.r' 'norm.r' 'numderiv.r'
'reshape.r' 'solve.r' 'sum.r' 'sums.r' 'theta.r'
'to_objective.r' 'trace.r' 'twomoments.r' 'vcov.r' 'vec.r'

'AllClass.r' 'bind.r' 'blockrep.r' 'coerce.r' 'data.r' 'det.r'
'diag.r' 'eigen.r' 'elwise.r' 'madness_pkg.r' 'matwise.r'
'max.r' 'norm.r' 'numderiv.r' 'Ops.r' 'reshape.r' 'solve.r'
'sum.r' 'sums.r' 'theta.r' 'to_objective.r' 'trace.r'
'twomoments.r' 'utils.r' 'vcov.r' 'vec.r'

Estimates average treatment effects using model average double robust (MA-DR) estimation. The MA-DR estimator is defined as weighted average of double robust estimators, where each double robust estimator corresponds to a specific choice of the outcome model and the propensity score model. The MA-DR estimator extend the desirable double robustness property by achieving consistency under the much weaker assumption that either the true propensity score model or the true outcome model be within a specified, possibly large, class of models.

May All Data be Reproducible and Transparent (MADRaT) *
c(person("Jan Philipp", "Dietrich", email = "dietrich@pik-potsdam.de", role = c("aut","cre")),
person("Lavinia", "Baumstark", email = "lavinia@pik-potsdam.de", role = "aut"),
person("Anastasis", "Giannousakis", email = "giannou@pik-potsdam.de", role = "aut"),
person("Benjamin Leon", "Bodirsky", email = "bodirsky@pik-potsdam.de", role = "ctb"),
person("Ulrich", "Kreidenweis", email = "bodirsky@pik-potsdam.de", role = "ctb"))
Provides a framework which should improve reproducibility and transparency in data processing. It provides functionality such as automatic meta data creation and management, rudimentary quality management, data caching, work-flow management and data aggregation.
* The title is a wish not a promise. By no means we expect this package to deliver everything what is needed to achieve full reproducibility and transparency, but we believe that it supports efforts in this direction.
spam, tools, utils, digest, methods, parallel, stringr
Jan Philipp Dietrich [aut, cre],
Lavinia Baumstark [aut],
Anastasis Giannousakis [aut],
Benjamin Leon Bodirsky [ctb],
Ulrich Kreidenweis [ctb]