
Summarise a correlation recovery into per-pair metrics
Source:R/classes.R
summary.bmmtools_cor_recovery.RdOne row per condition, pair, estimator and scale, summarised across
replications. Errors, coverage and the correlations are reported
against both truths: the generating correlation (bias, rmse,
coverage) and the correlation the simulated subjects had
(bias_sample, rmse_sample, coverage_sample, r, ccc).
Arguments
- object
A
bmmtools_cor_recoveryobject fromrecover_correlations().- ...
Not used.
Value
A bmmtools_cor_recovery_summary tibble with the columns
term, estimator, scale, n_replications, n_converged,
true_value, sample_sd, mean_estimate, bias, rmse,
bias_sample, rmse_sample, coverage, coverage_50,
coverage_sample, ci_width, ci_width_50, rejection_rate,
false_positive_rate, power, r, r_low, r_high, ccc,
ccc_low, ccc_high, z_mean, z_sd, z_mean_mcse and
z_sd_mcse, preceded by condition when the object
came from a grid. The z columns summarise the rows' z, as in
summary.bmmtools_recovery(); a correlation has no contraction in
this version. coverage_50 and ci_width_50 are the coverage of
the generating correlation and the mean width of the central 50 %
interval; they are NA when the estimates carry no such interval.
Details
true_value is the generating correlation when it is the same in
every replication and NA otherwise. sample_sd is the standard
deviation of the in-sample correlations across replications.
rejection_rate is the share of intervals that exclude zero. It is
reported as false_positive_rate when every true_value is 0 and as
power when none is. A true_value that is NA, which is what a
nonzero correlation becomes on the natural scale, counts as not 0, so
power is defined there. With a mix of zero and nonzero values both
are NA.
r (with a Fisher-z interval) and ccc (Lin's concordance, see
recovery_ccc()) compare the estimates with sample_value across
replications, one pair per replication. They are NA with fewer than
three replications or when either side has no spread.