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icensmis
View on CRAN: Click
here
Download and install icensmis package within the R console
Install from CRAN:
install.packages("icensmis")
Install from Github:
library("remotes")
install_github("cran/icensmis") Install by package version:
library("remotes")
install_version("icensmis", "1.5.0") Attach the package and use:
library("icensmis")
Maintained by
Xiangdong Gu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-11-26
Latest Update: 2021-09-02
Description:
We consider studies in which information from error-prone
diagnostic tests or self-reports are gathered sequentially to determine the
occurrence of a silent event. Using a likelihood-based approach
incorporating the proportional hazards assumption, we provide functions to
estimate the survival distribution and covariate effects. We also provide
functions for power and sample size calculations for this setting.
Please refer to Xiangdong Gu, Yunsheng Ma, and Raji Balasubramanian (2015)
, Xiangdong Gu and Raji Balasubramanian (2016)
, Xiangdong Gu, Mahlet G Tadesse, Andrea S Foulkes,
Yunsheng Ma, and Raji Balasubramanian (2020) .
How to cite:
Xiangdong Gu (2012). icensmis: Study Design and Data Analysis in the Presence of Error-Prone Diagnostic Tests and Self-Reported Outcomes. R package version 1.5.0, https://cran.r-project.org/web/packages/icensmis. Accessed 08 Mar. 2026.
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Other R packages that icensmis depends,
imports, suggests or enhances
Complete documentation for icensmis
Functions, R codes and Examples using
the icensmis R package
Some associated functions: bayesmc . datasim . fitsurv . icmis . icpower . icpower.val . icpower_weibull . icpowerpf . plot_surv .
Some associated R codes: HighDimCR.R . RcppExports.R . datasim.R . icmis.R . icpower.R . icpower.val.R . icpower_weibull.R . icpowerpf.R . Full icensmis package functions and examples
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