> I've started doing some analyses with hddm, and I stumble on a very basic
> and certainly very naive question about accuracy and stimulus coding: as I
> understand it, accuracy coding assumes that there is no bias, right? Then
> the drift rate will be positive whenever accuracy is above .5 and negative
> otherwise. But it makes no sense in this case to estimate a bias.
> This is what I understand from the topic "Code subject responses" where
> you write:
> "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 where 1 means left and 0 means right (this could also code
> for stimulus A and B instead of left and right). HDDM interprets 0 and 1
> responses as lower and upper boundary responses, respectively, so it has no
> preference one way or another."
> But then you go on saying that sometimes, of course, we may want to
> include a bias. Thus I infer that in accuracy coding, you do not try
> estimate a bias (meaning that it is fixed at .5*a or 0). And this is also
> what my intuition tells me: it makes no sense to have a bias leading to
> being correct!
Yes, that's exactly correct. What you can do alternatively though, is not
use accuracy coding but stimulus or direction coding and then estimate bias
because you can be biased to respond left, or to respond "face".
Thanks! but when I do stimulus coding, I must input the stimulus as an
independent variable (one more column in the data set) and make the drift
depend on it. But suppose I have no reason to believe that the absolute
value of the drift rate should be different in the two conditions, is there
a way I can enforce v_red = - v_green (in case I have two targets, one red
and one green)? If I don't do that, I will run into overfitting issues...
J.
On Fri, Oct 19, 2012 at 3:29 PM, Thomas Wiecki <Thomas_Wie...@brown.edu>wrote:
> On Fri, Oct 19, 2012 at 7:57 AM, Jerome Sackur <jerome.sac...@gmail.com>wrote:
>> Dear Thomas,
>> I've started doing some analyses with hddm, and I stumble on a very basic
>> and certainly very naive question about accuracy and stimulus coding: as I
>> understand it, accuracy coding assumes that there is no bias, right? Then
>> the drift rate will be positive whenever accuracy is above .5 and negative
>> otherwise. But it makes no sense in this case to estimate a bias.
>> This is what I understand from the topic "Code subject responses" where
>> you write:
>> "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 where 1 means left and 0 means right (this could also code
>> for stimulus A and B instead of left and right). HDDM interprets 0 and 1
>> responses as lower and upper boundary responses, respectively, so it has no
>> preference one way or another."
>> But then you go on saying that sometimes, of course, we may want to
>> include a bias. Thus I infer that in accuracy coding, you do not try
>> estimate a bias (meaning that it is fixed at .5*a or 0). And this is also
>> what my intuition tells me: it makes no sense to have a bias leading to
>> being correct!
> Yes, that's exactly correct. What you can do alternatively though, is not
> use accuracy coding but stimulus or direction coding and then estimate bias
> because you can be biased to respond left, or to respond "face".
> HTH,
> Thomas
>> All the best,
>> Thanks for making this great package available!
>> J.
>> --
>> Jérôme Sackur
>> Laboratoire de Sciences Cognitives et Psycholinguistique (ENS/CNRS/EHESS)
>> Département d'Etudes Cognitives
>> Ecole Normale Supérieure
>> 29, rue d'Ulm --- Pavillon Jardin
>> 75005 Paris, France
>> tel.: + 33 (0) 1 44 32 26 25
>> fax: + 33 (0) 1 44 32 26 30
>> email: jerome.sac...@gmail.com
-- Jérôme Sackur
Laboratoire de Sciences Cognitives et Psycholinguistique (ENS/CNRS/EHESS)
Département d'Etudes Cognitives
Ecole Normale Supérieure
29, rue d'Ulm --- Pavillon Jardin
75005 Paris, France
tel.: + 33 (0) 1 44 32 26 25
fax: + 33 (0) 1 44 32 26 30
email: jerome.sac...@gmail.com
On Fri, Oct 19, 2012 at 9:04 AM, Jerome Sackur <jerome.sac...@gmail.com>wrote:
> Thanks! but when I do stimulus coding, I must input the stimulus as an
> independent variable (one more column in the data set) and make the drift
> depend on it. But suppose I have no reason to believe that the absolute
> value of the drift rate should be different in the two conditions, is there
> a way I can enforce v_red = - v_green (in case I have two targets, one red
> and one green)? If I don't do that, I will run into overfitting issues...
Currently you can't enforce this, but this thread discusses a possible way
to code this up. I'm not sure if Guido actually implemented that or what
the status of that is.
> On Fri, Oct 19, 2012 at 3:29 PM, Thomas Wiecki <Thomas_Wie...@brown.edu>wrote:
>> Hi Jerome (cc'ing hddm mailing list),
>> On Fri, Oct 19, 2012 at 7:57 AM, Jerome Sackur <jerome.sac...@gmail.com>wrote:
>>> Dear Thomas,
>>> I've started doing some analyses with hddm, and I stumble on a very
>>> basic and certainly very naive question about accuracy and stimulus coding:
>>> as I understand it, accuracy coding assumes that there is no bias, right?
>>> Then the drift rate will be positive whenever accuracy is above .5 and
>>> negative otherwise. But it makes no sense in this case to estimate a bias.
>>> This is what I understand from the topic "Code subject responses" where
>>> you write:
>>> "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 where 1 means left and 0 means right (this could also code
>>> for stimulus A and B instead of left and right). HDDM interprets 0 and 1
>>> responses as lower and upper boundary responses, respectively, so it has no
>>> preference one way or another."
>>> But then you go on saying that sometimes, of course, we may want to
>>> include a bias. Thus I infer that in accuracy coding, you do not try
>>> estimate a bias (meaning that it is fixed at .5*a or 0). And this is also
>>> what my intuition tells me: it makes no sense to have a bias leading to
>>> being correct!
>> Yes, that's exactly correct. What you can do alternatively though, is not
>> use accuracy coding but stimulus or direction coding and then estimate bias
>> because you can be biased to respond left, or to respond "face".
>> HTH,
>> Thomas
>>> All the best,
>>> Thanks for making this great package available!
>>> J.
>>> --
>>> Jérôme Sackur
>>> Laboratoire de Sciences Cognitives et Psycholinguistique (ENS/CNRS/EHESS)
>>> Département d'Etudes Cognitives
>>> Ecole Normale Supérieure
>>> 29, rue d'Ulm --- Pavillon Jardin
>>> 75005 Paris, France
>>> tel.: + 33 (0) 1 44 32 26 25
>>> fax: + 33 (0) 1 44 32 26 30
>>> email: jerome.sac...@gmail.com
> --
> Jérôme Sackur
> Laboratoire de Sciences Cognitives et Psycholinguistique (ENS/CNRS/EHESS)
> Département d'Etudes Cognitives
> Ecole Normale Supérieure
> 29, rue d'Ulm --- Pavillon Jardin
> 75005 Paris, France
> tel.: + 33 (0) 1 44 32 26 25
> fax: + 33 (0) 1 44 32 26 30
> email: jerome.sac...@gmail.com
it is implemented and it works (thanks to Thomas patient explanations :-)!. I wanted to test it in a larger data set before posting it to the list, but we got a new cluster and installation of the required modules was delayed.
anyhow, I'll post the current method later tonight (European time)
Thomas Wiecki <Thomas_Wie...@brown.edu> wrote:
>On Fri, Oct 19, 2012 at 9:04 AM, Jerome Sackur
><jerome.sac...@gmail.com>wrote:
>> Thanks! but when I do stimulus coding, I must input the stimulus as
>an
>> independent variable (one more column in the data set) and make the
>drift
>> depend on it. But suppose I have no reason to believe that the
>absolute
>> value of the drift rate should be different in the two conditions, is
>there
>> a way I can enforce v_red = - v_green (in case I have two targets,
>one red
>> and one green)? If I don't do that, I will run into overfitting
>issues...
>Currently you can't enforce this, but this thread discusses a possible
>way
>to code this up. I'm not sure if Guido actually implemented that or
>what
>the status of that is.
>> J.
>> On Fri, Oct 19, 2012 at 3:29 PM, Thomas Wiecki
><Thomas_Wie...@brown.edu>wrote:
>>> Hi Jerome (cc'ing hddm mailing list),
>>> On Fri, Oct 19, 2012 at 7:57 AM, Jerome Sackur
><jerome.sac...@gmail.com>wrote:
>>>> Dear Thomas,
>>>> I've started doing some analyses with hddm, and I stumble on a very
>>>> basic and certainly very naive question about accuracy and stimulus
>coding:
>>>> as I understand it, accuracy coding assumes that there is no bias,
>right?
>>>> Then the drift rate will be positive whenever accuracy is above .5
>and
>>>> negative otherwise. But it makes no sense in this case to estimate
>a bias.
>>>> This is what I understand from the topic "Code subject responses"
>where
>>>> you write:
>>>> "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 where 1 means left and 0 means right (this could
>also code
>>>> for stimulus A and B instead of left and right). HDDM interprets 0
>and 1
>>>> responses as lower and upper boundary responses, respectively, so
>it has no
>>>> preference one way or another."
>>>> But then you go on saying that sometimes, of course, we may want to
>>>> include a bias. Thus I infer that in accuracy coding, you do not
>try
>>>> estimate a bias (meaning that it is fixed at .5*a or 0). And this
>is also
>>>> what my intuition tells me: it makes no sense to have a bias
>leading to
>>>> being correct!
>>> Yes, that's exactly correct. What you can do alternatively though,
>is not
>>> use accuracy coding but stimulus or direction coding and then
>estimate bias
>>> because you can be biased to respond left, or to respond "face".
>>> HTH,
>>> Thomas
>>>> All the best,
>>>> Thanks for making this great package available!
>>>> J.
>>>> --
>>>> Jérôme Sackur
>>>> Laboratoire de Sciences Cognitives et Psycholinguistique
>(ENS/CNRS/EHESS)
>>>> Département d'Etudes Cognitives
>>>> Ecole Normale Supérieure
>>>> 29, rue d'Ulm --- Pavillon Jardin
>>>> 75005 Paris, France
>>>> tel.: + 33 (0) 1 44 32 26 25
>>>> fax: + 33 (0) 1 44 32 26 30
>>>> email: jerome.sac...@gmail.com
>> --
>> Jérôme Sackur
>> Laboratoire de Sciences Cognitives et Psycholinguistique
>(ENS/CNRS/EHESS)
>> Département d'Etudes Cognitives
>> Ecole Normale Supérieure
>> 29, rue d'Ulm --- Pavillon Jardin
>> 75005 Paris, France
>> tel.: + 33 (0) 1 44 32 26 25
>> fax: + 33 (0) 1 44 32 26 30
>> email: jerome.sac...@gmail.com
-- Sent from my Android phone with K-9 Mail. Please excuse my brevity.
> On Fri, Oct 19, 2012 at 9:04 AM, Jerome Sackur
> <jerome.sac...@gmail.com <mailto:jerome.sac...@gmail.com>> wrote:
> Thanks! but when I do stimulus coding, I must input the stimulus
> as an independent variable (one more column in the data set) and
> make the drift depend on it. But suppose I have no reason to
> believe that the absolute value of the drift rate should be
> different in the two conditions, is there a way I can enforce
> v_red = - v_green (in case I have two targets, one red and one
> green)? If I don't do that, I will run into overfitting issues...
> Currently you can't enforce this, but this thread discusses a possible
> way to code this up. I'm not sure if Guido actually implemented that
> or what the status of that is.
> J.
> On Fri, Oct 19, 2012 at 3:29 PM, Thomas Wiecki
> <Thomas_Wie...@brown.edu <mailto:Thomas_Wie...@brown.edu>> wrote:
> Hi Jerome (cc'ing hddm mailing list),
> On Fri, Oct 19, 2012 at 7:57 AM, Jerome Sackur
> <jerome.sac...@gmail.com <mailto:jerome.sac...@gmail.com>> wrote:
> Dear Thomas,
> I've started doing some analyses with hddm, and I stumble
> on a very basic and certainly very naive question about
> accuracy and stimulus coding: as I understand it, accuracy
> coding assumes that there is no bias, right? Then the
> drift rate will be positive whenever accuracy is above .5
> and negative otherwise. But it makes no sense in this case
> to estimate a bias.
> This is what I understand from the topic "Code subject
> responses" where you write:
> "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 where 1 means left and 0 means right
> (this could also code for stimulus A and B instead of left
> and right). HDDM interprets 0 and 1 responses as lower and
> upper boundary responses, respectively, so it has no
> preference one way or another."
> But then you go on saying that sometimes, of course, we
> may want to include a bias. Thus I infer that in accuracy
> coding, you do not try estimate a bias (meaning that it is
> fixed at .5*a or 0). And this is also what my intuition
> tells me: it makes no sense to have a bias leading to
> being correct!
> Yes, that's exactly correct. What you can do alternatively
> though, is not use accuracy coding but stimulus or direction
> coding and then estimate bias because you can be biased to
> respond left, or to respond "face".
On Friday, October 19, 2012 3:30:14 PM UTC+2, Thomas Wiecki wrote:
> Hi Jerome (cc'ing hddm mailing list),
> On Fri, Oct 19, 2012 at 7:57 AM, Jerome Sackur <jerome...@gmail.com<javascript:>
> > wrote:
>> Dear Thomas,
>> I've started doing some analyses with hddm, and I stumble on a very basic >> and certainly very naive question about accuracy and stimulus coding: as I >> understand it, accuracy coding assumes that there is no bias, right? Then >> the drift rate will be positive whenever accuracy is above .5 and negative >> otherwise. But it makes no sense in this case to estimate a bias.
>> This is what I understand from the topic "Code subject responses" where >> you write:
>> "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 where 1 means left and 0 means right (this could also code >> for stimulus A and B instead of left and right). HDDM interprets 0 and 1 >> responses as lower and upper boundary responses, respectively, so it has no >> preference one way or another."
>> But then you go on saying that sometimes, of course, we may want to >> include a bias. Thus I infer that in accuracy coding, you do not try >> estimate a bias (meaning that it is fixed at .5*a or 0). And this is also >> what my intuition tells me: it makes no sense to have a bias leading to >> being correct!
> Yes, that's exactly correct. What you can do alternatively though, is not > use accuracy coding but stimulus or direction coding and then estimate bias > because you can be biased to respond left, or to respond "face".
> HTH,
> Thomas
>> All the best,
>> Thanks for making this great package available!
Good to see that it worked. Code seems pretty straight forward, thanks for
the contribution!. A couple of notes:
- I don't think you need all of those imports
- You probably don't have to overload create_knodes(). It's identical from
what I can tell.
- If you inherit from HDDM instead of HDDMBase you will get the new model
with transformations and Gibbs sampling.
I did those and some other changes and included the model in HDDM; the
develop branch now has a new model called HDDMStimCoding with some
documentation. I also updated the howto with some pointers on how to use
this new model:
> test_reduced.py is and example for how to run the overloaded hddm.
> InvZ.py is that script the loads hddm and created the overloaded method.
> I don't typically use python, so please excuse if the code isn't very
> clean (I don't) think it is to bad
> Cheers - Guido
> On Fri Oct 19 17:25:26 2012, Thomas Wiecki wrote:
>> On Fri, Oct 19, 2012 at 9:04 AM, Jerome Sackur
>> <jerome.sac...@gmail.com <mailto:jerome.sackur@gmail.**com<jerome.sac...@gmail.com>>>
>> wrote:
>> Thanks! but when I do stimulus coding, I must input the stimulus
>> as an independent variable (one more column in the data set) and
>> make the drift depend on it. But suppose I have no reason to
>> believe that the absolute value of the drift rate should be
>> different in the two conditions, is there a way I can enforce
>> v_red = - v_green (in case I have two targets, one red and one
>> green)? If I don't do that, I will run into overfitting issues...
>> Currently you can't enforce this, but this thread discusses a possible
>> way to code this up. I'm not sure if Guido actually implemented that
>> or what the status of that is.
>> J.
>> On Fri, Oct 19, 2012 at 3:29 PM, Thomas Wiecki
>> <Thomas_Wie...@brown.edu <mailto:Thomas_Wiecki@brown.**edu<Thomas_Wie...@brown.edu>>>
>> wrote:
>> Hi Jerome (cc'ing hddm mailing list),
>> On Fri, Oct 19, 2012 at 7:57 AM, Jerome Sackur
>> <jerome.sac...@gmail.com <mailto:jerome.sackur@gmail.**com<jerome.sac...@gmail.com>>>
>> wrote:
>> Dear Thomas,
>> I've started doing some analyses with hddm, and I stumble
>> on a very basic and certainly very naive question about
>> accuracy and stimulus coding: as I understand it, accuracy
>> coding assumes that there is no bias, right? Then the
>> drift rate will be positive whenever accuracy is above .5
>> and negative otherwise. But it makes no sense in this case
>> to estimate a bias.
>> This is what I understand from the topic "Code subject
>> responses" where you write:
>> "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 where 1 means left and 0 means right
>> (this could also code for stimulus A and B instead of left
>> and right). HDDM interprets 0 and 1 responses as lower and
>> upper boundary responses, respectively, so it has no
>> preference one way or another."
>> But then you go on saying that sometimes, of course, we
>> may want to include a bias. Thus I infer that in accuracy
>> coding, you do not try estimate a bias (meaning that it is
>> fixed at .5*a or 0). And this is also what my intuition
>> tells me: it makes no sense to have a bias leading to
>> being correct!
>> Yes, that's exactly correct. What you can do alternatively
>> though, is not use accuracy coding but stimulus or direction
>> coding and then estimate bias because you can be biased to
>> respond left, or to respond "face".
>> HTH,
>> Thomas
>> All the best,
>> Thanks for making this great package available!
>> J.
>> --
>> Jérôme Sackur
>> Laboratoire de Sciences Cognitives et Psycholinguistique
>> (ENS/CNRS/EHESS)
>> Département d'Etudes Cognitives
>> Ecole Normale Supérieure
>> 29, rue d'Ulm --- Pavillon Jardin
>> 75005 Paris, France
>> tel.: + 33 (0) 1 44 32 26 25
>> <tel:%2B%2033%20%280%29%201%**2044%2032%2026%2025>
hi thomS , thanks!
about create_knodes: I think I got an error message when I didn't include it. but maybe I was missing something else which caused that problem.
cheers-guido
PS: [very technical] do you have any experince with compiling pymc with the Intel MKL library? this should make a considerable difference on Intel processors (compared to atlas libraries) but due to lacking the experience I can't seem to find a way to point the setup to the Intel BLAS and LAPACK libraries...
Thomas Wiecki <thomas.wie...@gmail.com> wrote:
>Hi Guido,
>Good to see that it worked. Code seems pretty straight forward, thanks
>for
>the contribution!. A couple of notes:
>- I don't think you need all of those imports
>- You probably don't have to overload create_knodes(). It's identical
>from
>what I can tell.
>- If you inherit from HDDM instead of HDDMBase you will get the new
>model
>with transformations and Gibbs sampling.
>I did those and some other changes and included the model in HDDM; the
>develop branch now has a new model called HDDMStimCoding with some
>documentation. I also updated the howto with some pointers on how to
>use
>this new model:
>On Fri, Oct 19, 2012 at 1:37 PM, Guido Biele
><g.p.bi...@psykologi.uio.no>wrote:
>> Hi,
>> attached are 2 scripts.
>> test_reduced.py is and example for how to run the overloaded hddm.
>> InvZ.py is that script the loads hddm and created the overloaded
>method.
>> I don't typically use python, so please excuse if the code isn't very
>> clean (I don't) think it is to bad
>> Cheers - Guido
>> On Fri Oct 19 17:25:26 2012, Thomas Wiecki wrote:
>>> On Fri, Oct 19, 2012 at 9:04 AM, Jerome Sackur
>>> <jerome.sac...@gmail.com
><mailto:jerome.sackur@gmail.**com<jerome.sac...@gmail.com>>>
>>> wrote:
>>> Thanks! but when I do stimulus coding, I must input the stimulus
>>> as an independent variable (one more column in the data set) and
>>> make the drift depend on it. But suppose I have no reason to
>>> believe that the absolute value of the drift rate should be
>>> different in the two conditions, is there a way I can enforce
>>> v_red = - v_green (in case I have two targets, one red and one
>>> green)? If I don't do that, I will run into overfitting issues...
>>> Currently you can't enforce this, but this thread discusses a
>possible
>>> way to code this up. I'm not sure if Guido actually implemented that
>>> or what the status of that is.
>>> J.
>>> On Fri, Oct 19, 2012 at 3:29 PM, Thomas Wiecki
>>> <Thomas_Wie...@brown.edu
><mailto:Thomas_Wiecki@brown.**edu<Thomas_Wie...@brown.edu>>>
>>> wrote:
>>> Hi Jerome (cc'ing hddm mailing list),
>>> On Fri, Oct 19, 2012 at 7:57 AM, Jerome Sackur
>>> <jerome.sac...@gmail.com
><mailto:jerome.sackur@gmail.**com<jerome.sac...@gmail.com>>>
>>> wrote:
>>> Dear Thomas,
>>> I've started doing some analyses with hddm, and I stumble
>>> on a very basic and certainly very naive question about
>>> accuracy and stimulus coding: as I understand it, accuracy
>>> coding assumes that there is no bias, right? Then the
>>> drift rate will be positive whenever accuracy is above .5
>>> and negative otherwise. But it makes no sense in this case
>>> to estimate a bias.
>>> This is what I understand from the topic "Code subject
>>> responses" where you write:
>>> "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 where 1 means left and 0 means right
>>> (this could also code for stimulus A and B instead of left
>>> and right). HDDM interprets 0 and 1 responses as lower and
>>> upper boundary responses, respectively, so it has no
>>> preference one way or another."
>>> But then you go on saying that sometimes, of course, we
>>> may want to include a bias. Thus I infer that in accuracy
>>> coding, you do not try estimate a bias (meaning that it is
>>> fixed at .5*a or 0). And this is also what my intuition
>>> tells me: it makes no sense to have a bias leading to
>>> being correct!
>>> Yes, that's exactly correct. What you can do alternatively
>>> though, is not use accuracy coding but stimulus or direction
>>> coding and then estimate bias because you can be biased to
>>> respond left, or to respond "face".
>>> HTH,
>>> Thomas
>>> All the best,
>>> Thanks for making this great package available!
>>> J.
>>> --
>>> Jérôme Sackur
>>> Laboratoire de Sciences Cognitives et Psycholinguistique
>>> (ENS/CNRS/EHESS)
>>> Département d'Etudes Cognitives
>>> Ecole Normale Supérieure
>>> 29, rue d'Ulm --- Pavillon Jardin
>>> 75005 Paris, France
>>> tel.: + 33 (0) 1 44 32 26 25
>>> <tel:%2B%2033%20%280%29%201%**2044%2032%2026%2025>
