metadpy.utils.trialSimulation#

metadpy.utils.trialSimulation(d: float = 1.0, metad: float = 2.0, mRatio: float = 1, c: float = 0, nRatings: int = 4, nTrials: int = 500) → DataFrame[source]#

Simulate nR_S1 and nR_S2 response counts.

Parameters

dfloat: Type 1 task performance (d prime).
metadfloat: Type 2 sensitivity in units of type 1 dprime.
mRatiofloat: Specify Mratio (meta-d/d’). If len(mRatio)>1, mRatios are assumed to be drawn from a repeated measures design.
cfloat: Type 1 task bias (criterion).
nRatingsint: Number of ratings.
nTrialsint: Set the number of trials performed.

Returns

output_dfpandas.DataFrame: A DataFrame (nRows==`nTrials`) containing the responses and confidence rating for one participant given the provided parameters.