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r / packages / r-icensmis

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) <doi: 10.1214/15-AOAS810>, Xiangdong Gu and Raji Balasubramanian (2016) <doi: 10.1002/sim.6962>, Xiangdong Gu, Mahlet G Tadesse, Andrea S Foulkes, Yunsheng Ma, and Raji Balasubramanian (2020) <doi: 10.1186/s12911-020-01223-w>.

Type Size Name Uploaded Downloads Labels
conda 275.8 kB | linux-64/r-icensmis-1.5.0-r43h884c59f_0.tar.bz2  1 year and 1 month ago 23 main
conda 275.5 kB | linux-64/r-icensmis-1.5.0-r42h884c59f_0.tar.bz2  2 years and 7 months ago 52 main
conda 277.0 kB | win-64/r-icensmis-1.3.1-r36h796a38f_0.tar.bz2  4 years and 10 months ago 74 main
conda 289.0 kB | osx-64/r-icensmis-1.3.1-r36h466af19_0.tar.bz2  4 years and 10 months ago 19 main
conda 273.8 kB | linux-64/r-icensmis-1.3.1-r36h29659fb_0.tar.bz2  4 years and 10 months ago 64 main

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