This function derives statistics that can be calculated for model predictions and/or observed data. However, it does not calculate it, but rather calls the respective backend functions. Supported statistics currently include:
Basic Summary Statistics (i.e., means and response percentages
calc_basic_stats())
Conditional Accuracy Functions (CAFs; calc_cafs())
Quantiles (calc_quantiles())
Delta Functions (calc_delta_funs()).
Density Estimates (calc_dens()).
calc_stats_pred_obs(type, b_coding, conds, ..., scale_mass = FALSE)A data frame with the calculated statistic across conds
(ordered according to Source).
character string, specifying the type of statistic to calculate.
Available options are "basic_stats", "cafs", "quantiles",
"delta_funs", and "densities".
list for the boundary coding (see b_coding).
character vector, specifying the conditions to include in calculations (used for labeling and subsetting the model PDFs and the observed data).
Additional parameters passed on to the specific statistic calculation function (see Details).
a single logical, only relevant for density estimation.
If TRUE, PDF masses are scaled proportional to the number of trials per
condition.
When calling this function the arguments all_rts_u/all_rts_l and/or
all_pdfs must always be specified (see
re_evaluate_model, obs_data). Otherwise, the backend
functions won't work properly. Further arguments are:
for CAFS: n_bins controls the number of bins, with a default of 5.
for Quantiles and Delta Functions: probs controls the quantiles to
calculate. Default is seq(0.1, 0.9, 0.1)
(see drift_dm_default_probs()).
for basic summary satistics, Quantiles, and Delta Function:
skip_if_contr_low controls if quantiles and means are calculated for PDFs
with very small contribution (see also
drift_dm_skip_if_contr_low()).
for densities: discr controls the bin width for the observed data.
Default is 0.015 seconds
This function gets called by calc_stats()