icensmis: Study Design and Data Analysis in the Presence of Error-Prone Diagnostic Tests and Self-Reported Outcomes

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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.

Author
Xiangdong Gu and Raji Balasubramanian
Date of publication
2016-01-03 17:44:50
Maintainer
Xiangdong Gu <ustcgxd@gmail.com>
License
GPL (>= 2)
Version
1.3.1

View on CRAN

Man pages

datasim
Simulate data including multiple outcomes from error-prone...
icmis
Maximum likelihood estimation for settings of error-prone...
icpower
Study design in the presence of error-prone diagnostic tests...
icpowerpf
Study design in the presence of interval censored outcomes...
icpower.val
Study design in the presence of error-prone diagnostic tests...

Files in this package

icensmis
icensmis/tests
icensmis/tests/testthat.R
icensmis/tests/testthat
icensmis/tests/testthat/test_power.R
icensmis/src
icensmis/src/loglikC.cpp
icensmis/src/dataproc.cpp
icensmis/src/loglikA.cpp
icensmis/src/powerfuncs.cpp
icensmis/src/HighDimCR.cpp
icensmis/src/loglikB.cpp
icensmis/src/RcppExports.cpp
icensmis/NAMESPACE
icensmis/R
icensmis/R/HighDimCR.R
icensmis/R/icpower.R
icensmis/R/icmis.R
icensmis/R/datasim.R
icensmis/R/RcppExports.R
icensmis/R/icpower.val.R
icensmis/R/icpowerpf.R
icensmis/README.md
icensmis/MD5
icensmis/DESCRIPTION
icensmis/man
icensmis/man/icmis.Rd
icensmis/man/datasim.Rd
icensmis/man/icpower.Rd
icensmis/man/icpowerpf.Rd
icensmis/man/icpower.val.Rd