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Jun 28, 2026
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16 changes: 8 additions & 8 deletions DESCRIPTION
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Original file line number Diff line number Diff line change
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Package: CompCausal
Type: Package
Title: Inferring Causal Effects in Comprehensive Cohort Studies
Version: 0.0.9000
Version: 0.1.0
Depends:
R (>= 4.1.0)
Authors@R: c(
person(
"Jennifer", "Xu", email = "jennifer.xu@hsc.utah.edu", role = c("aut", "cre")
),
"Shiyao", "Xu", email = "jennifer.xu@hsc.utah.edu", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-1746-5977")),
person(given="George", family="Vega Yon", role=c("ctb"),
email="g.vegayon@gmail.com", comment = c(ORCID = "0000-0002-3171-0844")),
person("Daniel", "Scharfstein", , "daniel.scharfstein@hsc.utah.edu", role = c("pdr", "aut"),
comment = c(ORCID = "0000-0001-7482-9653"))
)
Description: Implementations of the estimation methods for
inferring causal effects in comprehensive cohort studies,
in the presence of unmeasured confounding and missing outcomes. The causal
effects include comprehensive cohort causal effects, randomized trial causal effects,
and patient preference causal effect.
Description: Implements semiparametric methods for estimating comprehensive cohort causal effects
in comprehensive cohort studies with unmeasured confounding in the observational arm
and outcomes that may be missing at random. The package provides tools for estimating
comprehensive cohort causal effects (CCCE), randomized trial causal effects (RTCE),
and patient preference causal effects (PPCE).
URL: https://github.com/UofUEpiBio/CompCausal, https://uofuepibio.github.io/CompCausal/
BugReports: https://github.com/UofUEpiBio/CompCausal/issues
License: MIT + file LICENSE
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