metadpy.utils.pairedResponseSimulation#

metadpy.utils.pairedResponseSimulation(d: float = 1.0, d_sigma: float = 0.1, mRatio: list = [1, 0.6], mRatio_sigma: float = 0.2, mRatio_rho: float = 0, c: float = 0, c_sigma: float = 0.1, nRatings: int = 4, nTrials: int = 500, nSubjects: int = 20) → DataFrame[source]#

Simulate response and confidence ratings a group with 2 experimental conditions.

Parameters

d: Type 1 task performance (d prime).
d_sigma: Include some between-subject variability for d prime.
mRatio: Specify Mratio (meta-d/d’). If len(mRatio)>1, mRatios are assumed to be drawn from a repeated measures design.
mRatio_sigma: Include some variability in the mRatio scores.
mRatio_rho: Specify the correlation between the two Mratios.
c: Type 1 task bias (criterion).
c_sigma: Include some between-subject variability for criterion.
nRatings: Number of ratings.
nTrials: Set the number of trials performed.
nSubjects: Specify the number of subject who performed the task. Defaults to 20.

Returns

output_df: A DataFrame (nRows==`nTrials` * nSubjects) containing the responses and confidence rating for one or many participants given the provided parameters.