BinNor-package {BinNor} | R Documentation |
Provides R functions for generating multiple binary and normal variables simultaneously given the marginal characteristics and association structure via combining well established results from the random number generation literature, based on the methodology proposed by Demirtas and Doganay (2012).
Package: | BinNor |
Type: | Package |
Version: | 2.3.3 |
Date: | 2021-03-05 |
License: | GPL-2 |
LazyLoad: | yes |
There are eight functions in this package. The functions lower.tri.to.corr.mat
,
validation.bin
, validation.nor
, validation.range
and validation.nor
are designed to prevent obvious specification errors and to validate the specified quantities. The most important functions are compute.sigma.star
, jointly.generate.binary.normal
and simulation
. The function compute.sigma.star
computes the matrix of tetrachoric correlations that will be used in
the generation of multivariate normal data whose some components are dichotomized to obtain binary variables.
The function jointly.generate.binary.normal
generates mixed data, and the function simulation
is capable of
repating this process many times and produces averages of some key statistical quantities across replications.
Anup Amatya, Hakan Demirtas, Ran Gao
Maintainer: Ran Gao <rgao8@uic.edu>
Demirtas, H., Doganay, B. (2012). Simultaneous generation of binary and normal data with specified marginal and association structures. Journal of Biopharmaceutical Statistics; 22(2), 223-236.
Demirtas, H., Amatya, A., and Doganay, B. (2014). BinNor: An R package for con-current generation of binary and normal data. Communications in Statistic-Simulation
and Computation; 43(3), 569-579.