fit_dd()
:
"mazur"
/"hyperbolic"
or "exponential"
) and methods ("pooled"
, "mean"
, or "two stage"
)."fit_dd"
containing the fitted models, input data, and method details.plot_dd()
:
results_dd()
:
"fit_dd"
object.check_unsystematic()
:
calc_aucs()
:
calc_conf_int()
function, ensuring accurate estimation based on model degrees of freedom.calc_r2()
function, providing reliable fit metrics for all models.check_unsystematic
), model fitting (fit_dd
), to visualization (plot_dd
), to result extraction
(results_dd
).calc_pd()
and score_pd()
. ep50
changed to etheta50
and corrected calculation of ep50
.calc_pd()
(and score_pd()
, timing_pd()
, and ans_pd
).score_dd()
that would unintentionally drop all rows if both conditions were FALSE
.Rename example data from five.fivetrial
to five.fivetrial_dd
for delay discounting.
Add example data five.fivetrial_pd
for probability discounting.
score_mcq27()
properly supports arguments: impute_method
, random
, return_data
, and verbose
.
See documentation and the README
for explanations.
generate_data_mcq()
can generate fake MCQ data, including seed
and prop_na
arguments for
reproducibility and specifying proportion of NA
s.
long_to_wide*
and wide_to_long*
are helper functions to reshape data from/to different formats.
NA
s exist in the data, score_mcq27()
returns NA
s for the scoring
instead of 1.Initial release with basic scoring of 27-item Monetary Choice Questionnaire and 5.5 trial delay discounting task from the Qualtrics template.
Added a NEWS.md
file to track changes to the package.