Overview | Installation | A minimal example | Inspecting the fit: print() | Per-score view: summary() | Visualising: plot() | The fitted object | Next steps | References

Overview | Example 1: A binary educational test, verifying Lord (1955) | Adding bootstrap standard errors | Example 2: A dichotomous educational test, comparing estimators (SAT12) | Example 3: A Likert personality scale, smoother and D-study | D-study: projecting to a different test length | References

Overview | Installation | A minimal example | Inspecting the fit: print() | Per-score view: summary() | Visualising: plot() | The fitted object | Next steps | References

Overview | Example 1: A binary educational test, verifying Lord (1955) | Adding bootstrap standard errors | Example 2: A dichotomous educational test, comparing estimators (SAT12) | Example 3: A Likert personality scale, smoother and D-study | D-study: projecting to a different test length | References

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

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

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

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

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

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

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

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

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

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