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