Package: personnelSelectionUtility 1.0.2

personnelSelectionUtility: Utility Analysis Methods for Personnel Selection

Implements classical and contemporary utility-analysis methods for personnel selection, organised by criterion scale (classification or continuous/monetary) and selection structure (compensatory or multiple-hurdle). Methods include Taylor-Russell classification (Taylor and Russell, 1939, <doi:10.1037/h0057079>), Brogden-Cronbach-Gleser monetary utility (Brogden, 1949, <doi:10.1111/j.1744-6570.1949.tb01397.x>), Schmidt-Hunter-Pearlman intervention utility (Schmidt and others, 1979, <doi:10.1037/0021-9010.64.6.609>), Sturman comprehensive cascade (Sturman, 2001, <doi:10.1108/eb029072>), Thomas-Owen-Gunst multivariate classification (Thomas and others, 1977, <doi:10.3102/10769986002001055>), compensatory versus multiple-hurdle simulation (Ock and Oswald, 2018, <doi:10.1027/1866-5888/a000205>), AUC-to-effect-size conversions (Salgado, 2018, <doi:10.5093/ejpalc2018a5>), Pareto frontiers for validity-diversity trade-offs, and Monte Carlo uncertainty propagation.

Authors:René Gempp [aut, cre, cph]

personnelSelectionUtility_1.0.2.tar.gz
personnelSelectionUtility_1.0.2.zip(r-4.7-any)personnelSelectionUtility_1.0.2.zip(r-4.6-any)personnelSelectionUtility_1.0.2.zip(r-4.5-any)
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personnelSelectionUtility_1.0.2.tar.gz(r-4.7-any)personnelSelectionUtility_1.0.2.tar.gz(r-4.6-any)
personnelSelectionUtility_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
personnelSelectionUtility/json (API)

# Install 'personnelSelectionUtility' in R:
install.packages('personnelSelectionUtility', repos = c('https://rgempp.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/rgempp/personnelselectionutility/issues

Pkgdown/docs site:https://gempp.cl

On CRAN:

Conda:

4.88 score 393 downloads 62 exports 1 dependencies

Last updated from:74f4c7242a. Checks:9 OK. Indexed: yes.

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linux-develOK112
source / vignettesOK191
linux-releaseOK107
macos-releaseOK168
macos-oldrelOK208
windows-develOK70
windows-releaseOK81
windows-oldrelOK67
wasm-releaseOK89

Exports:adverse_impact_ratioargument_glossaryauc_to_d_equal_varianceauc_to_point_biserialauc_to_rauc_to_rank_biserialbcg_utilityboudreau_utilitybreak_even_validitycoefficient_of_determinationcompare_selection_systemscompare_selection_systems_stagedcompensatory_selectioncomposite_dcor_to_dcorrect_r_direct_range_restrictioncorrect_r_lawleyd_to_cord_to_point_biserialdisattenuate_correlationdominance_analysisemployee_flowforecasting_efficiencyfuse_composite_corfuse_reliabilityfuse_validitygroup_tr_multivariateincremental_validityinflation_adjusted_ratemodel_taxonomymultiattribute_utilitymultiple_hurdle_selectionmultiple_hurdle_selection_stagednaylor_shineoffer_rejection_adjustmentpareto_frontierprobation_adjustmentprobation_utilityrelative_weightsrestricted_canonical_validityrisk_adjusted_utilitysdy_cost_accountingsdy_crepidsdy_observedsdy_percentilesdy_proportionalsdy_rbnsdy_superior_equivalentsselected_mean_zselection_tableselection_utility_from_zsensitivity_gridshp_utilitysturman_comprehensivetr_binomial_success_probabilitytr_classictr_multivariatetr_multivariate_equal_cutofftr_solveutility_fairness_frontierutility_monte_carloutility_regression_diagnostics

Dependencies:mvtnorm

Compensatory versus multiple-hurdle selection simulation
The design question | A four-predictor example | Compensatory selection | Staged multiple-hurdle selection | Direct comparison | Cost-reliability trade-off | Offer rejection: Murphy (1986) | Adverse impact and the validity-diversity dilemma | Multi-attribute utility | Risk-adjusted utility | How to proceed in applied work | References
Rendered fromcompensatory-vs-multiple-hurdle-simulation.Rmdusingknitr::rmarkdown

Last update: 2026-05-05
Started: 2026-05-04

Continuous and monetary utility: Naylor-Shine, BCG, Boudreau, and Sturman
From success ratios to continuous performance | Brogden-Cronbach-Gleser monetary utility | The baseline problem | Estimating $SD_y$: the four families | Cost accounting | Global percentile | Proportional rules | Individualised methods | Triangulation | Schmidt-Hunter-Pearlman intervention utility | Boudreau-style extensions | Composite formation | Range-restriction corrections | Incremental validity and predictor importance | The integrated Sturman comprehensive model | How to proceed in applied work | References
Rendered fromcontinuous-monetary-utility-bcg-boudreau-sturman.Rmdusingknitr::rmarkdown

Last update: 2026-05-05
Started: 2026-05-04

Reproducing canonical examples from the literature
Purpose | Conventions: illustrative versus digit-for-digit | Schmidt, Hunter, McKenzie, and Muldrow (1979): the Programmer Aptitude Test | Murphy (1986): the cost of rejected offers | Holling (1998): normality, outliers, and $SD_y$ | Sturman (2000, 2001): the comprehensive cascade | Step-by-step cascade | The cumulative cascade | Single integrated call | Ock and Oswald (2018): compensatory versus multiple-hurdle | Parameter setup | Run the comparison at three selection ratios | Tabulate | Adding the cost dimension | How to proceed in applied work | References
Rendered fromreproductions.Rmdusingknitr::rmarkdown

Last update: 2026-05-05
Started: 2026-05-05

Taylor-Russell and the Thomas-Owen-Gunst multivariate extension
The classificatory problem | Solving unknown Taylor-Russell inputs | Why the univariate model is not enough | Multivariate Taylor-Russell with specified marginal cutoffs | Equal-cutoff tables and target joint selection ratio | Group-specific multivariate Taylor-Russell | Finite sampling | Reproducing Thomas-Owen-Gunst (1977), Table 6 | How to proceed in applied work | References
Rendered fromtaylor-russell-and-thomas-owen-gunst.Rmdusingknitr::rmarkdown

Last update: 2026-05-05
Started: 2026-05-04

Utility-analysis taxonomy for personnel selection
Purpose | The two-by-two taxonomy | Why the choice of cell matters | Argument naming and conventions | Recommended workflow | Step 1: Specify the selection decision | Step 2: Specify the criterion scale | Step 3: Specify the baseline | Step 4: Estimate or triangulate $SD_y$ | Step 5: Report uncertainty and sensitivity | Minimal examples by model family | Dichotomous success criterion | Continuous criterion | Effect-size conversions | Reporting checklist | How to proceed in applied work | References
Rendered fromutility-analysis-taxonomy.Rmdusingknitr::rmarkdown

Last update: 2026-05-05
Started: 2026-05-04

Readme and manuals

Help Manual

Help pageTopics
Adverse-impact ratio by groupadverse_impact_ratio
Argument naming glossaryargument_glossary
Convert AUC to Cohen's d under the equal-variance binormal modelauc_to_d_equal_variance
Convert AUC to a point-biserial correlationauc_to_point_biserial
Convert AUC to a rank-biserial correlationauc_to_rank_biserial
Brogden-Cronbach-Gleser utilitybcg_utility
Boudreau-style discounted utilityboudreau_utility
Break-even validity for BCG utilitybreak_even_validity
Coefficient of determinationcoefficient_of_determination
Compare compensatory and conjunctive multiple-hurdle selection systemscompare_selection_systems
Compare compensatory and staged multiple-hurdle selection systemscompare_selection_systems_staged
Expected performance under compensatory top-down selectioncompensatory_selection
Composite effect size for a weighted predictor batterycomposite_d
Convert a correlation to Cohen's dcor_to_d
Direct range-restriction correction for selection on the predictorcorrect_r_direct_range_restriction
Multivariate range-restriction correction (Lawley, 1943)correct_r_lawley
Convert Cohen's d to a correlationd_to_cor
Convert Cohen's d to a point-biserial correlationd_to_point_biserial
Disattenuated correlation (Spearman, 1904)disattenuate_correlation
Dominance analysis for predictor importancedominance_analysis
Compute employee flows across periodsemployee_flow
Forecasting efficiencyforecasting_efficiency
Correlation matrix between several weighted compositesfuse_composite_cor
Reliability of a weighted composite (Mosier, 1943; Lord & Novick, 1968)fuse_reliability
Correlation of a weighted composite with an external variablefuse_validity
Multigroup multivariate Taylor-Russell summariesgroup_tr_multivariate
Incremental validity for adding predictors to an existing systemincremental_validity
Combine nominal discount and inflation ratesinflation_adjusted_rate
Utility-analysis model taxonomymodel_taxonomy
Multi-attribute utilitymultiattribute_utility
Simulate conjunctive multiple-hurdle selectionmultiple_hurdle_selection
Simulate staged multiple-hurdle selection with composite stagesmultiple_hurdle_selection_staged
Naylor-Shine expected criterion gainnaylor_shine
Offer-rejection adjustment for selection utility (Murphy, 1986)offer_rejection_adjustment
Pareto frontier indicatorpareto_frontier
Expected standardized performance after a probation cutoffprobation_adjustment
Utility with a probation-period survivor adjustmentprobation_utility
Johnson relative weights for one criterionrelative_weights
Restricted canonical validity for a fixed criterion compositerestricted_canonical_validity
Risk-adjusted utilityrisk_adjusted_utility
SDy from cost-accounting datasdy_cost_accounting
SDy from a simplified CREPID-style activity decompositionsdy_crepid
Observed SDy from monetary criterion datasdy_observed
Estimate SDy from percentile judgmentssdy_percentile
Estimate SDy with proportional rulessdy_proportional
Estimate SDy with a coefficient-of-variation approachsdy_rbn
SDy from superior-equivalents judgmentssdy_superior_equivalents
Expected standardized predictor score among selected applicantsselected_mean_z
Selection table and classification metricsselection_table
Selection utility from expected standardized criterion performanceselection_utility_from_z
Sensitivity grid for BCG utilitysensitivity_grid
Schmidt-Hunter-Pearlman intervention utilityshp_utility
Sturman's (2001) comprehensive utility analysissturman_comprehensive
Binomial sampling probabilities for Taylor-Russell success ratestr_binomial_success_probability
Taylor-Russell utility for one predictortr_classic
Multivariate Taylor-Russell utility for conjunctive multiple-hurdle selectiontr_multivariate
Solve equal marginal cutoffs for a target joint selection ratiotr_multivariate_equal_cutoff
Solve one Taylor-Russell parameter from the other threetr_solve
Utility-fairness Pareto frontierutility_fairness_frontier
Monte Carlo uncertainty propagation for BCG utilityutility_monte_carlo
Basic utility-analysis regression diagnosticsutility_regression_diagnostics