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.

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>.

c(person(given = "David",
family = "Epstein",
role = c("aut"),
email = "davidepstein@ugr.es",
comment = c(ORCID = "0000-0002-2275-0916")),
person(given = "Daniel",
family = "Perez-Troncoso",
role = c("aut","cre"),
email = "danielperez@ugr.es",
comment = c(ORCID = "0000-0003-0091-8148")))
The app will calculate the ICER (incremental cost-effectiveness
ratio) Rawlins (2012) <doi:10.1016/B978-0-7020-4084-9.00044-6> from the mean
costs and quality-adjusted life years (QALY) Torrance and Feeny (2009) <doi:10.1017/S0266462300008461>
for a set of treatment options, and draw the efficiency frontier
in the costs-effectiveness plane. The app automatically identifies
and excludes dominated and extended-dominated options from the ICER
calculation.
shiny, shinythemes, purrr, DT, tidyverse, readxl, ggplot2,
ggrepel, digest, shinyhelper
David Epstein [aut] (<https://orcid.org/0000-0002-2275-0916>),
Daniel Perez-Troncoso [aut, cre]
(<https://orcid.org/0000-0003-0091-8148>)