icensmis package - RDocumentation

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icensmis

This is an R package for Study Design and Data Analysis in the Presence of Error-Prone Diagnostic Tests and Self-Reported Outcomes. Please refer to our Annals of Applied Statistics paper, Statistics in Medicine paper, and BMC Medical Informatics and Decision Making paper for more details of proposed methods.

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Version

Install

install.packages('icensmis')

Monthly Downloads

221

Version

1.5.0

License

GPL (>= 2)

Maintainer

Xiangdong Gu

Last Published

September 2nd, 2021

Functions in icensmis (1.5.0)

Bayesian method for high-dimensional variable selection

Fit survival function, used for Bayesian simulation

Maximum likelihood estimation for settings of error-prone diagnostic tests and self-reported outcomes

Study design in the presence of error-prone diagnostic tests and self-reported outcomes when sensitivity and specificity are unkonwn and a validation set is used

Study design in the presence of interval censored outcomes (assuming perfect diagnostic tests)

Study design in the presence of error-prone diagnostic tests and self-reported outcomes

icpower_weibull

Study design in the presence of error-prone diagnostic tests and self-reported outcomes for Weibull model

Plot survival function

Simulate data including multiple outcomes from error-prone diagnostic tests or self-reports