Title: Summary Measures for Clinical Trials with Survival Outcomes
Description: Provides estimates of the several summary measures for clinical trials including
the average hazard ratio, the weighted average hazard ratio, the restricted
superiority probability ratio, the restricted mean survival difference and
the ratio of restricted mean times lost, based on the short-term and
long-term hazard ratio model (Yang, 2005 <doi:10.1093/biomet/92.1.1>)
which accommodates various non-proportional hazards scenarios. The inference
procedures and the asymptotic results for the summary measures are discussed

Description: Provides estimates of several summary measures for clinical trials including

Title: Recalibration Methods for Improved Clinical Utility of Risk
Description: Recalibrate risk scores (predicting binary outcomes) to improve clinical utility of risk score using weighted logistic or constrained logistic recalibration methods. Additionally, produces plots to assess the potential for recalibration to improve the clinical utility of a risk model. Methods are described in detail in Mishra, A. (2019) "Methods for Risk Markers that Incorporate Clinical Utility" <http://hdl.handle.net/1773/44068>.
Imports: lattice, caret, ggplot2, stats, cowplot, nloptr

Description: Clique percolation community detection for weighted and
unweighted networks as well as threshold and plotting functions.
person("Jens", "Lange", email = "lange.jens@outlook.com",
person("Janis", "Zickfeld", role = c("ctb")))
Imports: colorspace, graphics, igraph, magrittr, Matrix, methods,
Packaged: 2019-10-22 12:09:44 UTC; Jens Lange

person("Janis", "Zickfeld", role = c("ctb")),
person("Alexander P.", "Christensen", role = c("ctb")))
Polychrome, qgraph, stats, utils, parallel, pbapply
Packaged: 2021-05-29 09:27:55 UTC; Jens Lange

person("Alexander P.", "Christensen", role = c("ctb")),
person("Pedro Henrique Ribeiro", "Santiago", role = c("ctb")))
Polychrome, qgraph, stats, utils, parallel, lessR, ohenery,

Title: Seeking and Finding Clones in Copy Number and Sequencing Data
Description: Defines the classes and functions used to simulate and
to analyze data sets describing copy number variants and,
optionally, sequencing mutations in order to detect clonal subsets.
See Zucker et al. (2019) <doi:10.1093/bioinformatics/btz057>.
Imports: methods, graphics, combinat, gtools, quantmod