Summarize a population-level design forecast

Summarize a population-level design forecast

Usage

# S3 method for class 'mfrm_population_prediction'
summary(object, digits = 3, ...)

Arguments

object

Output from predict_mfrm_population().

digits

Number of digits used in numeric summaries.

...

Reserved for generic compatibility.

Value

An object of class summary.mfrm_population_prediction with:

• design: requested future design

• overview: run-level overview

• forecast: facet-level forecast table

• facet_names: public non-person facet names used in the forecast

• design_variable_aliases: public aliases for design variables

• design_descriptor: role-based description of design variables

• planning_scope: explicit record of the current planning contract

• planning_constraints: explicit record of mutable/locked design variables

• planning_schema: structured planning metadata

• gpcm_boundary: bounded-GPCM caveat row when present

• structural_design_review: deterministic structural review of the named-facet design grid; it is not a forecast-uncertainty result

• ademp: simulation-study metadata

• notes: interpretation notes

See also

predict_mfrm_population()

Examples

# \donttest{
spec <- build_mfrm_sim_spec(
  n_person = 16,
  n_rater = 3,
  n_criterion = 2,
  raters_per_person = 2,
  assignment = "rotating"
)
pred <- predict_mfrm_population(
  sim_spec = spec,
  design = list(person = 18),
  reps = 1,
  maxit = 30,
  seed = 123
)
#> Warning: Unknown or uninitialised column: `ConvergenceRate`.
#> Warning: Unknown or uninitialised column: `MeanMinCategoryCount`.
#> Warning: Unknown or uninitialised column: `MeanSeparation`.
s <- summary(pred)
s$overview
#> # A tibble: 1 × 5
#>   Designs Replications SuccessfulRuns ConvergedRuns MeanElapsedSec
#>     <dbl>        <dbl>          <dbl>         <dbl>          <dbl>
#> 1       1            1              1             1           1.08
s$forecast[, c("Facet", "MeanSeparation", "McseSeparation")]
#> # A tibble: 3 × 3
#>   Facet     MeanSeparation McseSeparation
#>   <chr>              <dbl>          <dbl>
#> 1 Criterion           0                NA
#> 2 Person              1.36             NA
#> 3 Rater               0                NA
# }