Author: Richard Cotton [aut, cre], Janko Thyson [ctb]
Authors@R: c(person("Richard", "Cotton", role = c("aut", "cre"),
email = "richierocks@gmail.com"), person("Janko", "Thyson", role = "ctb"))
Description: Utilities for paths, files and directories.

Imports: assertive, plyr, stringr (>= 1.0.0)

Imports: assertive.base (>= 0.0-3), assertive.properties,
assertive.strings, plyr, stringr (>= 1.0.0), utils

Imports: assertive.base (>= 0.0-3), assertive.files, assertive.numbers,
assertive.types, magrittr, plyr, stringi, utils
Suggests: knitr, rmarkdown, testthat, withr

Packaged: 2017-02-15 13:50:33 UTC; richierocks

Title: An Imputation Approach to Estimating Path-Specific Causal
person("Minh", "Trinh", email = "mdtrinh@mit.edu", role = "cre"),
person("Teppei", "Yamamoto", email = "teppei@mit.edu", role = "aut"),
person("Xiang", "Zhou", email = "xiang_zhou@fas.harvard.edu", role = "aut"))
Description: In causal mediation analysis with multiple causally ordered mediators, a set of path-specific
effects are identified under standard ignorability assumptions. This package implements an imputation
approach to estimating these effects along with a set of bias formulas for conducting sensitivity analysis
(Zhou and Yamamoto <doi:10.31235/osf.io/2rx6p>). It contains two main functions: paths() for estimating
path-specific effects and sens() for conducting sensitivity analysis. Estimation uncertainty is quantified
Imports: BART, boot, gbm, ggplot2, metR, parallel, pryr, stats, twang,
Packaged: 2020-05-04 02:30:00 UTC; Minh Trinh

Imports: BART, boot, gbm, ggplot2, metR, pryr, stats, twang, tidyr
Packaged: 2021-06-17 23:51:34 UTC; Minh Trinh

Title: Wrangle, Analyze, and Visualize Animal Movement Data
Description: Tools to import, clean, and visualize movement data,
particularly from motion capture systems such as Optitrack's
'Motive', the Straw Lab's 'Flydra', or from other sources. We provide
functions to remove artifacts, standardize tunnel position and tunnel
axes, select a region of interest, isolate specific trajectories, fill
gaps in trajectory data, and calculate 3D and per-axis velocity. For
experiments of visual guidance, we also provide functions that use
subject position to estimate perception of visual stimuli.
Imports: R.matlab, data.table (>= 1.12.2), magrittr (>= 1.5), dplyr (>=
Author: Vikram B. Baliga [aut, cre] (<https://orcid.org/0000-0002-9367-8974>),
Melissa S. Armstrong [aut] (<https://orcid.org/0000-0002-3059-0094>),