Administers the MST under five policies to the same examinees:
- cold
Full routing module, population prior for routing and scoring.
- prior_route
Full routing module, student's interim prior for routing only; population prior for the reported score.
- prior_both
Interim prior for routing and for the reported score.
- prior_short
Interim prior for routing with a shortened routing module (`short_n` items); population prior for scoring.
- prior_only
Route on the interim prior alone (no routing module); population prior for scoring.
Arguments
- mst
A `ty_mst`.
- theta
True summative abilities.
- prior
Student priors (`mean`, `sd`) from `predict()` on a `ty_link`.
- population
Population prior `c(mean, sd)`; default: moments of the student priors' implied marginal.
- short_n
Routing items for `prior_short`.
- seed
Optional seed (each policy gets its own stream).
Examples
sim <- ty_simulate(n_calibration = 300, n_operational = 300, seed = 1)
op <- sim[sim$cohort == "operational", ]
prior <- predict(ty_link(sim), op)
pol <- ty_policies(ty_mst_default(), op$theta_S, prior, seed = 1)
summary(pol)
#> policy n routing_accuracy routed_too_easy routed_too_hard mean_items
#> 1 cold 300 0.73 0.12000000 0.15000000 36
#> 2 prior_route 300 0.87 0.05000000 0.08000000 36
#> 3 prior_both 300 0.86 0.05666667 0.08333333 36
#> 4 prior_short 300 0.83 0.06666667 0.10333333 30
#> 5 prior_only 300 0.82 0.07000000 0.11000000 24
#> bias rmse mean_se
#> 1 -0.010955884 0.3519350 0.3488391
#> 2 -0.006595008 0.3514604 0.3461850
#> 3 0.009668233 0.2565423 0.2559708
#> 4 0.012397010 0.3756825 0.3723276
#> 5 -0.021422683 0.4211025 0.4077246