Skip to contents

[Experimental]

Usage

verdict_table(result)

Arguments

result

A bmmtools_validation.

Value

A tibble with stage, title, required, status (the stage's), criterion (the bar in words), value (the number judged), pass (TRUE, FALSE, or NA when the stage did not run or the criterion cannot be evaluated) and note.

Details

One row per criterion, with the bar written out, so a card can print the criterion next to its verdict rather than a bare pass or fail.

The criteria are the plan's (see validation_plan(), "Criteria"):

  • prior predictive: the largest floor or ceiling rate under the calibration's prior (or bmm's defaults when the calibration uses them) at most prior_bound_rate_max; not judged for a response without a known range.

  • SBC: no ranked variable outside the sbc_ecdf_prob simultaneous ECDF band, and no failed check (a high Rhat, a low rank ESS or missing diagnostics) in any fit. The value is the number of failed checks, so a fit that fails two counts twice.

  • computation: the share of converged cells at least convergence_rate_min.

  • recovery: the coverage of every population parameter, pooled over the designs, not below coverage_level by a one-sided binomial test at coverage_alpha divided by the number of parameters. The coverage of each design is reported, not judged.

  • identifiability: at the largest design, every population parameter's mean contraction above contraction_min and its mean z-score within z_mean_max of 0.

  • individual differences: the coverage of every generating correlation held to the same pooled test, divided by the number of correlations.

  • data requirements: every subject-varying parameter reaches r_low >= read_off_r_low within the grid at read_off_n_subjects subjects, the value being the largest read-off over the parameters; a parameter the grid gave no person-level correlation is not judged. Its coverage leg is the recovery criterion's pooled test, repeated as a second row: a per-design coverage bar changed or removed a calibrated ezdm model's read-off in 24 % to 56 % of runs at 10 replications.

  • agreement: reported, not judged.

The ECDF band is simultaneous over the ranks of one variable; it is not corrected for the number of variables, so with more ranked variables a calibrated model leaves some band more often.