The per-factor block of the accompanying paper: modal and mean number
of defining sorts per posterior draw with a credible interval, the
selected flag count, the mean posterior spread of the statement
scores, and the mean replicate reliability
R_i = s_i^2 / (1 + s_i^2) of the flagged participants. The
statement-score correlations between factors ride along as an
attribute.
Arguments
- fit
A
bayesqm_fit.- prob
Credible-interval probability for the defining-sort counts (default 0.90).
- q, floor
The flag rule fixing the flagged set, as in
compute_flags().
Value
A data frame with one row per factor: factor, flagged
(selected flags), defining_modal, defining_mean,
defining_lower, defining_upper, score_spread, and
reliability. Attribute score_correlations holds the posterior
mean K x K correlation matrix of the statement scores.
Examples
factor_characteristics(demo_fit())
#> factor flagged defining_modal defining_mean defining_lower defining_upper
#> 1 f1 0 4 3.585 2 5
#> 2 f2 0 2 2.265 1 4
#> score_spread reliability
#> 1 0.4153759 NA
#> 2 0.5072720 NA