c(
person("Maya B.", "Mathur", email = "mmathur@stanford.edu", role = c("cre", "aut")),
person("Louisa H.", "Smith", role = "aut"),
person("Peng", "Ding", role = "aut"),
person("Tyler J.", "VanderWeele", role = "aut"))
stats, graphics, ggplot2 (>= 2.2.1), metafor, msm, devtools,
methods
Maya B. Mathur [cre, aut],
Louisa H. Smith [aut],
Peng Ding [aut],
Tyler J. VanderWeele [aut]

Sensitivity Analyses for Unmeasured Confounding and Other Biases
in Observational Studies and Meta-Analyses
Conducts sensitivity analyses for unmeasured confounding,selection bias, and measurement error (individually or in combination) in individual studies. Also conducts sensitivity analyses for unmeasured confounding in meta-analyses.
stats, graphics, ggplot2 (>= 2.2.1), metafor, methods, boot,
MetaUtility, dplyr

Conducts sensitivity analyses for unmeasured confounding, selection bias, and measurement error (individually or in combination; VanderWeele & Ding (2017) <doi:10.7326/M16-2607>; Smith & VanderWeele (2019) <doi:10.1097/EDE.0000000000001032>; VanderWeele & Li (2019) <doi:10.1093/aje/kwz133>; Smith & VanderWeele (2021) <arXiv:2005.02908>). Also conducts sensitivity analyses for unmeasured confounding in meta-analyses (Mathur & VanderWeele (2020a) <doi:10.1080/01621459.2018.1529598>; Mathur & VanderWeele (2020b) <doi:10.1097/EDE.0000000000001180>) and for additive measures of effect modification (Mathur et al., under review).

stats, graphics, ggplot2 (>= 2.2.1), metafor, metadat,
methods, boot, MetaUtility, dplyr

Goodness-of-fit tests for the Exponential and two-parameter
Weibull distributions
This package contains a large number of the goodness-of-fit tests for the Exponential and Weibull distributions classified into families: the tests based on the empirical distribution function, the tests based on the probability plot, the tests based on the normalized spacings, the tests based on the Laplace transform and the likelihood based tests ...

This package contains a large number of the goodness-of-fit tests for the Exponential and Weibull distributions classified into families: the tests based on the empirical distribution function, the tests based on the probability plot, the tests based on the normalized spacings, the tests based on the Laplace transform and the likelihood based tests.