rMOST

rMOST-package

Estimates Pareto-optimal solution for personnel selection with 3 objectives using Normal Boundary Intersection (NBI) algorithm introduced by Das and Dennis (1998) tools:::Rd_expr_doi("10.1137/S1052623496307510"). Takes predictor intercorrelations and predictor-objective relations as input and generates a series of solutions containing predictor weights as output. Accepts between 3 and 10 selection predictors. Maximum 2 objectives could be adverse impact objectives. Partially modeled after De Corte (2006) TROFSS Fortran program <a href="https://users.ugent.be/~wdecorte/trofss.pdf">https://users.ugent.be/~wdecorte/trofss.pdf</a> and updated from 'ParetoR' package described in Song et al. (2017) tools:::Rd_expr_doi("10.1037/apl0000240"). For details, see Study 3 of Zhang et al. (in press).

internal

Estimates Pareto-optimal solution for personnel selection
with 3 objectives using Normal Boundary Intersection (NBI) algorithm
introduced by Das and Dennis (1998) <doi:10.1137/S1052623496307510>.
Takes predictor intercorrelations and predictor-objective relations as
input and generates a series of solutions containing predictor weights
as output. Accepts between 3 and 10 selection predictors. Maximum 2
objectives could be adverse impact objectives. Partially modeled after
De Corte (2006) TROFSS Fortran program
<https://users.ugent.be/~wdecorte/trofss.pdf> and updated from
'ParetoR' package described in Song et al. (2017)
<doi:10.1037/apl0000240>. For details, see Study 3 of Zhang et al. (2023).

Chelsea Song

Estimates Pareto-Optimal Solution for Hiring with 3 Objectives

Yesuel Kim

rMOST-package function

Maintainer: Chelsea Song <a href="/link/qianqisong%40gmail.com?package=rMOST&version=1.0.1" data-mini-rdoc="rMOST::qianqisong@gmail.com">qianqisong@gmail.com</a> (<a href="https://orcid.org/0000-0003-0910-1281">ORCID</a>)
Other contributors:<ul>
<li>Yesuel Kim <a href="/link/kimyesuel97%40gmail.com?package=rMOST&version=1.0.1" data-mini-rdoc="rMOST::kimyesuel97@gmail.com">kimyesuel97@gmail.com</a> (<a href="https://orcid.org/0000-0002-8486-7693">ORCID</a>) [contributor]</li>
</ul>

Author

Estimates Pareto-optimal solution for personnel selection with 3 objectives using Normal Boundary Intersection (NBI) algorithm introduced by Das and Dennis (1998) tools:::Rd_expr_doi("10.1137/S1052623496307510"). Takes predictor intercorrelations and predictor-objective relations as input and generates a series of solutions containing predictor weights as output. Accepts between 3 and 10 selection predictors. Maximum 2 objectives could be adverse impact objectives. Partially modeled after De Corte (2006) TROFSS Fortran program <a href='https://users.ugent.be/~wdecorte/trofss.pdf'>https://users.ugent.be/~wdecorte/trofss.pdf</a> and updated from 'ParetoR' package described in Song et al. (2017) tools:::Rd_expr_doi("10.1037/apl0000240"). For details, see Study 3 of Zhang et al. (in press).

rMOST: Estimates Pareto-Optimal Solution for Hiring with 3 Objectives — rMOST-package

Maintainer: Chelsea Song <a href='mailto:qianqisong@gmail.com'>qianqisong@gmail.com</a> (<a href='https://orcid.org/0000-0003-0910-1281'>ORCID</a>)
Other contributors:<ul>
<li>Yesuel Kim <a href='mailto:kimyesuel97@gmail.com'>kimyesuel97@gmail.com</a> (<a href='https://orcid.org/0000-0002-8486-7693'>ORCID</a>) [contributor]</li>
</ul>

rMOST-package: rMOST: Estimates Pareto-Optimal Solution for Hiring with 3 Objectives

Description

Arguments

Author