Correct encoding for binary choice data #184
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filippoferrari
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Hi @filippoferrari , so we probably need to create a response function to handle this kind of design, The |
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Hi,
I have a one armed-bandit task where, on each trial, an agent sees two stimuli A and B, chooses one of them and receives a reward with probability p(chosen) = 1-p(not chosen), i.e., at each trial one of the stimuli will lead to a reward.
My data is stored as follows where
choice=0
shows outcomeA andoutcome=0/1
is nothing/win respectively,win
being whether the chosen stimuli leads to a winI am trying to estimate parameters using a binary hgf like as follows (based on the multilevel tutorial)
I have tried various encoding:
input_data = outcomeA
,response_function_inputs = choice
input_data = win
,response_function_inputs = choice
, this should be the same as the contingency space encoding described in the tapas HGF manual.pdfbut neither of these encodings seem to produce sensible parameters estimates for tonic_volatility_2 and inverse_temperature (the pymc model is defined similarly to the parameter recovery tutorial).
In particular, I get all estimated values for the inverse_temperature to be 0<x<0.1, which makes me believe that the input data and response must be mismatched making the model behave randomly.
What is the correct way to encode this type of data?
Thanks,
Filippo
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