> I have some questions about this.  If accuracy coding is used, movement of
> the starting point bias does not impact the response distributions in the
> same manner as if the data were stimulus coded.  For example, in the case
> of Exp3 in the Ratcliff & McKoon paper, upwards bias in z increases the
> relative probability of reaching the A bound and decreases the probability
> of reaching the alternative bound.  If the data are accuracy coded the
> probability of correctly identifying each alternative increases, despite
> the experimental manipulation of one having a higher prior probability of
> occurring. Am I missing something crucial here?

> Best,

> Kyle

> On Monday, September 10, 2012 11:21:20 AM UTC-4, Guido Biele wrote:

>> hi thomas,

>> glad that we are agree!
>> I never exclude that I am missing something ;-)

>> I'll think about something for the how to, but I first want to test a
>> few things, because I think that this issues is really not so trivial
>> ...

>> cheers - guido

>> On Mon Sep 10 17:17:04 2012, Thomas Wiecki wrote:
>> > Hi Guido,

>> > On Mon, Sep 10, 2012 at 11:04 AM, Guido Biele
>> > <g.p....@psykologi.uio.no <mailto:g.p....@psykologi.**uio.no>> wrote:

>> >     In your response you mention using a hybrid. I agree with the
>> >     approach, even if I don't understand why you call it
>> >     stimulus-coding, because 1 is always associated with the correct
>> >     response, and not always with "left response" or always with
>> >     "right response".*

>> > You are right, in fact it's accuracy (upper is correct) and stimulus
>> > (upper is left/right, depending on condition) coding simultaneously.

>> >     More generally, when the data are from a task where correct and
>> >     incorrect responses can be determined, I think one should always
>> >     use accuracy coding, so that one can estimate the difficulty of a
>> >     condition (or capability of a participant/group). I am not sure
>> >     what the meaning of the drift rate would be if the data were
>> >     stimulus/direction-coded.

>> > Agreed. I suppose I haven't thought too much about these issues
>> > because in our tasks there is no reason to assume a bias so I always
>> > use accuracy coding.

>> > It does seems as if the hybrid should always be preferred over pure
>> > stimulus coding so maybe a convenience function to recode the
>> > responses to be in accordance this would be handy. This might also be
>> > better described in the howto. Let me know if you want to give either
>> > of those a crack.

>> > Thomas

>> >     Cheers - Guido

>> >     *c.f. your documentation: "There are two ways you can code subject
>> >     responses (these are the values you put in the ‘response’ column
>> >     in your data file). You can either use accuracy-coding where 1
>> >     means correct and 0 means error, or you can use direction-coding
>> >     [GB: which i understand meaning the same as stimulus-coded] where
>> >     1 means left and 0 means right ..."

>> >     On Mon Sep 10 15:23:34 2012, Thomas Wiecki wrote:

>> >>     Hi,

>> >>     I couldn't find those passages:

>> >>     From White: "position of starting point relative to the
>> >>     boundaries (values
>> >>     above .5 indicate bias to respond ‘‘word’’ and values below .5
>> >>     indicate bias to respond ‘‘nonword""

>> >>     From McKoon where they introduce response bias in exp 3: "Because
>> >>     the
>> >>     proportions of the two stimuli tested for the high- versus
>> >>     low-probability stimuli produced an asymmetry between re- sponses
>> in
>> >>     accuracy of the two responses and also RTs for correct responses
>> and
>> >>     error responses, they were not combined as they were for
>> >>     experiments 1
>> >>     and 2."

>> >>     You could use a hybrid (I think they do this in the last
>> experiment
>> >>     where they have 2 conditions: left correct, right correct (i.e.
>> >>     stimulus coding)).

>> >>     In left correct you could code left to represent the upper
>> boundary
>> >>     (i.e. 1) and in right correct you could code right to represent
>> the
>> >>     upper boundary. This way upper boundary would always be correct
>> but
>> >>     you are still using stimulus coding. That way positive drift would
>> >>     always mean >50% accuracy.

>> >>     I think it is helpful to think about this in terms of which
>> boundary
>> >>     you want to mean what and that bias is relative to those
>> boundaries.
>> >>     HDDM just estimates whatever you present it with.

>> >>     Thomas

>> >>     On Mon, Sep 10, 2012 at 8:49 AM, Guido Biele
>> >>     <g.p....@psykologi.uio.no <mailto:g.p....@psykologi.**uio.no>
>> >>     <mailto:g.p....@psykologi.**uio.no>
>> >>     <mailto:g.p....@psykologi.**uio.no>> wrote:

>> >>     Hi,

>> >>     first thanks for publishing a new, improved version oh hddm!

>> >>     the hddm manual suggests that one should not accuracy-code ata
>> >>     when estimating a response bias.
>> >>     diverging from this recommendation, I just stumbled about 2 papers
>> >>     by ratcliff and colleagues, who do exactly this.*
>> >>     is the recommendation (to not accuracy code for experiments with a
>> >>     response bias) due to a reason that has to do specifically with
>> hddm?

>> >>     Ratcliff and McKoon (2008) examine if prior probability influences
>> >>     the starting point or the drift rate. to test the effect on drift
>> >>     rate, they seem to decompose the total drift rate into 2
>> >>     components, one due to stimulus quality and one due to prior
>> >>     probability.
>> >>     Is this kind of analysis possible in the new version of hddm?
>> >>     (I am happy to do some additional coding myself if this is
>> >>     required to get this working)

>> >>     Cheers - guido

>> >>     * see
>> >>     (a) White, C. N., Ratcliff, R., Vasey, M. W., & McKoon, G.
>> >>     (2010). Using diffusion models to understand clinical disorders.
>> >>     /Journal of Mathematical Psychology/, /54/(1), 39–52.

>> >>     page 42, section 4.1
>> >>     (b) Ratcliff, R., & McKoon, G. (2008). The diffusion decision
>> >>     model: theory and data for two-choice decision tasks. /Neural
>> >>     Computation/, /20/(4), 873–922. doi:10.1162/neco.2008.12-06-**420
>> >>     page 897, section 4.3

>> >     --
>> >     ------------------------------**------------------------------**----------- -

>> >       Guido Biele
>> >       Email:g...@psykologi.uio.**no  <mailto:g.p....@psykologi.**uio.no>

>> >       Phone:+47 228 45172  <tel:%2B47%20228%2045172>
>> >       Website  <https://sites.google.com/a/**
>> neuro-cognition.org/guido/home<https://sites.google.com/a/neuro-cognition.org/guido/home>
>> **>

>> >       Visiting Address
>> >       Psykologisk Institutt
>> >       Forskningsveien 3 A
>> >       0373 OSLO

>> >        Mailing Address
>> >        Psykologisk Institutt
>> >        Postboks 1094
>> >        Blindern 0317 OSLO

>> --
>> ------------------------------**------------------------------**----------- -

>>   Guido Biele
>>   Email: g.p....@psykologi.uio.no
>>   Phone: +47 228 45172
>>   Website  <https://sites.google.com/a/**neuro-cognition.org/guido/home<https://sites.google.com/a/neuro-cognition.org/guido/home>
>> **>

>>   Visiting Address
>>   Psykologisk Institutt
>>   Forskningsveien 3 A
>>   0373 OSLO

>>    Mailing Address
>>    Psykologisk Institutt
>>    Postboks 1094
>>    Blindern 0317 OSLO