Description: Estimation of quantile regression models for survival data. The package implements the two-step estimator described in Frumento and Bottai (2017),  <doi: 10.1016/j.csda.2016.08.015>.
Packaged: 2020-03-15 11:55:20 UTC; Paolo Frumento

Packaged: 2021-02-01 12:27:24 UTC; Paolo Frumento

Title: Retrieve and Analyze Information on Clinical Trials from Public
Imports: mongolite (>= 2.0), jsonlite, httr, curl, clipr, xml2, rvest
SystemRequirements: mongo database, sed, php, cat, perl
Description: Provides functions for querying, retrieving and analysing protocol- and results-related information on clinical trials from two public registers, the European Union Clinical Trials Register (EUCTR, <https://www.clinicaltrialsregister.eu/>) and ClinicalTrials.gov (CTGOV, <https://clinicaltrials.gov/>). The information is transformed and then stored in a database (mongo). Functions are provided for accessing and analysing the locally stored information on the clinical trials, as well as for identifying duplicate records. The package is motivated by the need for aggregating and trend-analysing the design, conduct and outcomes across clinical trials.
Suggests: testthat, devtools, knitr, rmarkdown
Packaged: 2019-03-07 11:18:40 UTC; ralfherold
Author: Ralf Herold [aut, cre] (<https://orcid.org/0000-0002-8148-6748>)

Packaged: 2019-03-27 20:24:08 UTC; ralfherold

Packaged: 2019-04-30 09:07:55 UTC; ralfherold

Packaged: 2019-04-11 19:58:47 UTC; ralfherold

Title: Retrieve and Analyze Clinical Trials in Public Registers
Imports: jsonlite, httr, curl, clipr, xml2, rvest, nodbi (>= 0.3)
Description: Provides functions for querying, retrieving and analysing
protocol- and results-related information on clinical trials from
two public registers, the European Union Clinical Trials Register
information is transformed and then stored in a database (nodbi).
Functions are provided for accessing and analysing the locally
stored information on the clinical trials, as well as for
identifying duplicate records. The package is motivated by the need
for aggregating and trend-analysing the design, conduct and outcomes
Suggests: devtools, knitr, rmarkdown, RSQLite (>= 2.1.2), mongolite,
Authors@R: person(given = "Ralf", family = "Herold", role = c("aut", "cre"),
email = "ralf.herold@mailbox.org", comment = c(ORCID =
Packaged: 2019-10-22 22:17:48 UTC; ralfherold