Reference-Based Multiple Imputation for Ordinal/Binary Response
c(person("Ying", "Liu", role = c("aut")),
person("Tony", "Wang", email="xwang@imedacs.com", role = c("aut", "cre"),
comment = c(ORCID="0000-0002-6760-5456")))
Reference-based multiple imputation of ordinal and binary responses under Bayesian
framework, as described in Wang and Liu (2022) <arXiv:2203.02771>. Methods for
missing-not-at-random include Jump-to-Reference (J2R), Copy Reference (CR), and Delta
Adjustment which can generate tipping point analysis.
JointAI, rjags, coda, foreach, data.table, future, doFuture,
mathjaxr, survival, ggplot2, ordinal, progressr, Matrix,
mcmcse, reshape2
knitr, rmarkdown, bookdown, ggpubr, testthat (>= 3.0.0),
spelling
Ying Liu [aut],
Tony Wang [aut, cre] (<https://orcid.org/0000-0002-6760-5456>)

JointAI, rjags, coda, foreach, data.table, future, doFuture,
mathjaxr, survival, ggplot2, ordinal, progressr, Matrix, mcmcse
knitr, rmarkdown, bookdown, R.rsp, ggpubr, testthat (>=
3.0.0), spelling

remix provides remix, a quick and easy function for
describing datasets. It can be view as a mix of cast (in
package reshape) and summary.formula (in package Hmisc).
'factor.r' 'numeric.r' 'parse.r' 'rbind.r' 'remix.r'

'correlation.r' 'freq.r' 'funs.r' 'na.r' 'parse.r' 'rbind.r'
'remix.r' 'summarize.by.r' 'summarize.r' 'table.r' 'tabular.r'

'correlation.r' 'element.r' 'freq.r' 'funs.r' 'na.r' 'parse.r'
'rbind.r' 'remix.r' 'summarize.by.r' 'summarize.r' 'survival.r'
'table.r' 'tabular.r' 'test.r'

'remote' is short for "R(-based) EMpirical Orthogonal TEleconnections".
It implements a collection of functions to facilitate empirical
orthogonal teleconnection analysis. Empirical Orthogonal Teleconnections
(EOTs) denote a regression based approach to decompose spatio-temporal
fields into a set of independent orthogonal patterns. They are quite
similar to Empirical Orthogonal Functions (EOFs) with EOTs producing
less abstract results. In contrast to EOFs, which are orthogonal in both
space and time, EOT analysis produces patterns that are orthogonal in
either space or time.
R (>= 2.10), Rcpp (>= 0.10.3), raster, foreach, methods
maps, lattice, latticeExtra, grid, gridExtra, sp