Emulation of an application originally created by Paul Pukite. Computer Aided Rate Modeling and Simulation.  Jan Pukite and Paul Pukite, (1998, ISBN 978-0-7803-3482), William J. Stewart, (1994, ISBN: 0-691-03699-3).

Compute covariate-adjusted specificity at controlled sensitivity level, or covariate-adjusted sensitivity at controlled specificity level, or covariate-adjust receiver operating characteristic curve, or covariate-adjusted thresholds at controlled sensitivity/specificity level. All statistics could also be computed for specific sub-populations given their covariate values. Methods are described in Ziyi Li, Yijian Huang, Datta Patil, Martin G. Sanda (2021+) "Covariate adjustment in continuous biomarker assessment".

This R-extension package contains dozens of functions useful
 for: database style joins [nerge()] & aggregation [bestBy(), groupBy() & regroup()],
 database migration [dbWriteTable2()], file I/O [write.delim(), read.tab()], 
 text parsing / data mining [m()], data structure conversion [nv(), tab2df()], 
 summarizing & reporting [pct(), fit.1ln.rprt()], character string manipulation [m() & pad()],
 legend table making [sstable() & leghead()] & plot placement [legend.position()],  
 plot annotation [labsegs() & mvlabs()], data visualization [pies(), spie(), & heatmatrix()], 
 and data exploration [hyperplot(), plot.xy.ab.p()], batch scripting [parseArgString()].
 The package's greatest contributions stem from its database style merge, 
 aggregation and interface functions as well as in it's extensive
 use and propagation of row, column and vector names in most functions. 
 The latest additions are plotting functions [confound.grid() & sparge()] that intake 
 a dataframe & formulas to visually resolve variable confounding (Simpson, 1951).

Mainly used to build tables that are commonly presented for
    bio-medical/health research, such as basic characteristic tables or
    descriptive statistics.

Sending functions to remote processes can be wasteful of
    resources because they carry their environments with them. With the
    carrier package, it is easy to create functions that are isolated from
    their environment. These isolated functions, also called crates, print
    at the console with their total size and can be easily tested locally
    before being sent to a remote.