tidygraph, igraph, network, shiny, plyr, survey, tidyr,
methods, utils, purrr, rlang

knitr, testthat (>= 2.1.0), rmarkdown, haven

tidygraph, igraph, network, shiny, survey, tidyr, methods,
utils, purrr, rlang

tidygraph, igraph, network, shiny, srvyr, tidyr, methods,
utils, purrr, rlang
knitr, testthat (>= 2.1.0), rmarkdown, survey, haven

c(
person("Till", "Krenz", email = "egor@tillt.net",
role = c("aut", "cre")),
person("Pavel N.", "Krivitsky", email="pavel@statnet.org",
role=c("aut")),
person("Raffaele", "Vacca", email = "r.vacca@ufl.edu",
role = c("aut")),
person(given = "Michal",
family = "Bojanowski",
role = "aut",
email = "michal2992@gmail.com",
comment = c(ORCID = "0000-0001-7503-852X")),
person("Markus", "Gamper", email = "m.gamper@uni-koeln.de",
role = c("ctb")),
person("Andreas", "Herz", email = "herzand@uni-hildesheim.de",
role = c("aut")),
person("Christopher", "McCarty", email = "ufchris@ufl.edu",
role = c("ctb")))
Till Krenz [aut, cre],
Pavel N. Krivitsky [aut],
Raffaele Vacca [aut],
Michal Bojanowski [aut] (<https://orcid.org/0000-0001-7503-852X>),
Markus Gamper [ctb],
Andreas Herz [aut],
Christopher McCarty [ctb]

tidygraph, srvyr, tidyr, methods, utils, purrr, rlang
knitr, testthat (>= 2.1.0), rmarkdown, survey, shiny, igraph,
network, haven

A package for survival and event history analysis.

A package for survival and event history analysis

Event History Analysis and Discrete Models
A package for the analysis event history, binary, and
count data.

Event history analysis: Sampling of risk sets in Cox
regression, selections in the Lexis diagram, bootstrapping.
Parametric proportional hazards fitting with left truncation
and right censoring for common families of distributions,
piecewise constant hazards, and discrete models. AFT regression
for left truncated and right censored data. Binary and Poisson
regression for clustered data, fixed and random effects with
bootstrapping.
R (>= 2.13.0), stats, graphics, utils, survival

Event history analysis: Sampling of risk sets in Cox regression,
selections in the Lexis diagram, bootstrapping. Parametric
proportional hazards fitting with left truncation and right
censoring for common families of distributions, piecewise
constant hazards, and discrete models. AFT regression for
left truncated and right censored data. Binary and Poisson
regression for clustered data, fixed and random effects with
bootstrapping.