CMAverse/DESCRIPTION at master · BS1125/CMAverse · GitHub

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Package: CMAverse
Type: Package
Title: Causal Mediation Analysis
Version: 0.1.0
URL: https://bs1125.github.io/CMAverse/, https://github.com/BS1125/CMAverse
Authors@R: c(
    person("Baoyi", "Shi", role = c("aut", "cre"), email = "bs3141@columbia.edu"),
    person("Ziqing", "Wang", role = c("aut", "crb"), email = "zw2899@cumc.columbia.edu"),
    person("Christine", "Choirat", role = "aut", email = "cchoirat@gmail.com"),
    person("Linda", "Valeri", role = "aut", email = "lv2424@cumc.columbia.edu")
    )
Maintainer: Baoyi Shi <bs3141@cumc.columbia.edu>, Ziqing Wang <zw2899@cumc.columbia.edu>
Description: CMAverse provides a suite of functions for reproducible causal mediation
    analysis including DAG visualization, statistical modeling and sensitivity analysis. It
    implements six causal mediation analysis approaches including the regression-based
    approach by Valeri et al. (2013) <doi: 10.1037/a0031034> and VanderWeele et al. (2014)
    <doi: 10.1515/em-2012-0010>, the weighting-based approach by VanderWeele et al. (2014)
    <doi: 10.1515/em-2012-0010>, the inverse odd-ratio weighting approach by Tchetgen Tchetgen
    (2013) <doi: 10.1002/sim.5864>, the natural effect model by Vansteelandt et al. (2012)
    <doi: 10.1515/2161-962X.1014>, the marginal structural model by VanderWeele
    et al. (2017) <doi: 10.1111/rssb.12194>, and the g-formula approach for a single time point
    exposure and multiple mediators allowing for time varying confounders by Robins (1986)
    <doi: 10.1016/0270-0255(86)90088-6>. Moreover, CMAverse conducts sensitivity analysis for
    unmeasured confounding via the E-value approach by VanderWeele et al. (2017)
    <doi: 10.7326/M16-2607> and Smith et al. (2019) <doi: 10.1097/EDE.0000000000001064>, and
    sensitivity analysis for measurement error via regression calibration by Carroll et al. (1995)
    <doi: 10.1201/9781420010138> and SIMEX by Cook et al. (1994) <doi: 10.2307/2290994> and
    Küchenhoff et al. (2006) <doi: 10.1111/j.1541-0420.2005.00396.x>. CMAverse also supports
    causal mediation analysis for a case control study. When the dataset contains missing values,
    CMAverse can conduct multiple imputations for causal mediation analysis.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports:
    ggdag,
    stringr,
    simex,
    dplyr,
    mice,
    nnet,
    MASS,
    survey,
    survival,
    SuppDists,
    boot,
    msm,
    Matrix,
    EValue,
    ggplot2,
    doSNOW,
    foreach,
    medflex,
    mstate,
    predint,
    survminer
RoxygenNote: 7.3.1
Suggests:
    knitr,
    tidyverse,
    kableExtra,
    dagitty,
    rmarkdown,
    testthat,
    covr
VignetteBuilder: knitr
Depends: R (>= 2.10)
BugReports: https://github.com/BS1125/CMAverse/issues