# a clear step-by-step procedure?

**URL:** <http://discourse.iapct.org/t/a-clear-step-by-step-procedure/12927>\
**Category:** CSG2018\
**Created:** [April 30, 2018, 6:19pm UTC](http://discourse.iapct.org/t/a-clear-step-by-step-procedure/12927 "2018-04-30T18:19:26Z")\
**Posts on this page:** 1\
**Showing post:** 13

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**Author:** ![bnhpct](http://discourse.iapct.org/user_avatar/discourse.iapct.org/bnhpct/32/34_2.png) [@bnhpct](http://discourse.iapct.org/u/bnhpct)\
**Post date:** [November 1, 2019, 8:33pm UTC](http://discourse.iapct.org/t/a-clear-step-by-step-procedure/12927/13 "2019-11-01T20:33:40Z")

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[Bruce Nevin (20191101.16:30 ET)]

Probably Alex is no longer looking for a clear step-by-step specification of the Test, but on the assumption that the question will arise again I have put Billʽs specification (as rephased by Phil Runkel) on the Discourse forum under Methodlogy at [http://discourse.iapct.org/t/the-test-for-the-controlled-variable/134](http://discourse.iapct.org/t/the-test-for-the-controlled-variable/134).

> **···**
>
> > /Bruce
> 
> On Wed, May 2, 2018 at 12:13 AM Martin Taylor [mmt-csg@mmtaylor.net](mailto:mmt-csg@mmtaylor.net) wrote:
> 
> > [Martin Taylor 2018.04.30.15.05]
> 
> > ```
> > On 2018/04/30 2:29 PM, Alex Gomez-Marin > wrote:
> > 
> > ```
> 
> > > i’d still appreciate a clear TCV step-by-step.
> 
> > >
> 
> > > …
> > > 
> > > > ```
> > > > Hey,
> > > > 
> > > > ```
> > > > 
> > > > Adam and I are trying to take the TCV seriously,  
> > > > but we would like to have it in a clear logical  
> > > > step-by-step way so that it is concrete. I know  
> > > > these has been around there in many papers, but  
> > > > I wonder if someone could just share the  
> > > > “cooking recipe” so as to be clear when a  
> > > > variable _can_ be ruled out as a  
> > > > controlled variable, and when it can still be  
> > > > one (although one is never sure it _must_  
> > > > be). Thanks, Alex
> 
> > > >
> 
> > ```
> > As with must such questions, I doubt that there is a black-and-white
> > 
> > ```
> > 
> > all-purpose answer to this. So let’s take a PCT-based approach: (1)  
> > ask what you are trying to achieve, (2) Ask how your perception of  
> > the situation differs from how you would like it to be (what you are  
> > trying to achieve), (3) Ask if you have a means to make your  
> > perception closer to its reference value (what you are trying to  
> > achieve). You are starting with question (3), which leads to a  
> > different way of thinking. It is like saying “I have this thing  
> > called a screwdriver . Now what can I do with it?”. The answer would  
> > be “if you have a screw of the right type, you can use it and the  
> > screw to attach one thing to another.” “But what is ‘the right  
> > type’?” “If the things are wood, you want a wood screw, but if they  
> > are metal, you want a metal screw.”
> > 
> > ```
> > Enough analogy. The TCV is a tool that can be used for related but
> > 
> > ```
> > 
> > different purposes, and the step-by-step instructions depend on what  
> > you want to achieve. All of them depend on finding a way to disturb  
> > some possibly controlled perception by way of disturbing a variable  
> > in the environment of the organism that might be responsible for the  
> > perception you hypothesise. But after than, there are various  
> > possibilities. The Runkel sequence that was linked a while back is  
> > one of them. (Bruce Nevin [Bruce Nevin 2018-05-01\_08:20:48 ET]  
> > reposted it today.
> > 
> > ```
> > You say you want to know whether a particular variable V in the
> > 
> > ```
> > 
> > environment does or does not correspond to a controlled perception.  
> > You do not say whether this variable lies on a continuum of similar  
> > hypotheses such as V = Xp+Yq , where p and q  
> > are exponents that may take on a range of values your theory  
> > permits, or whether it is of a category that differs cleanly from  
> > other categories that might sensibly be hypothesized to be “the”  
> > controlled variable (the wood screw versus the metal screw).
> > 
> > ```
> > Powers required two preliminary tests as prerequisites to performing
> > 
> > ```
> > 
> > the TCV (or as part of it), so I’ll include them as steps 1 and 2,  
> > in either order. I will call the hypothesized corresponding  
> > controlled quantity in the environment “V”.
> > 
> > ```
> > 1. Could the subject plausibly perceive the value V?
> > 
> > 2. Could the subject act deliberately to influence the value V?
> > 
> > The answers to these questions may be evident, but if not, then
> > 
> > ```
> > 
> > finding the answers provides two steps of the TCV. For example, in  
> > the case of the speed-curvature relation, it is not plausible that  
> > the subject could perceive the power relation while acting in a way  
> > that produces it, so it cannot be a controlled variable, and must be  
> > a side effect of controlling something else.
> > 
> > ```
> > From here on, the steps of the TCV depend on whether the question is
> > 
> > ```
> > 
> > a Yes-No (YN) question, a Forced-Choice question (FC) or an unforced  
> > choice question (UC). These three choices apply mainly to cases in  
> > which the hypothesised variable is categorical. If V is continuous,  
> > the TCV becomes an optimization problem. In each situation, you need  
> > to find a way of disturbing the hypothesized V, but your choice  
> > depends on the question.
> > 
> > ```
> > It doesn't matter what your question, the TCV will always have one
> > 
> > ```
> > 
> > or all of three problems. The first problem is that the subject’s  
> > reference value may change for the controlled perception that is the  
> > object of your Test, which has the effect of adding noise into your  
> > measurements; the second is that the subject may stop actively  
> > controlling that perception during your test; and the third is the  
> > contextual dependence problem that is simplified in the X+Y+Z  
> > example below, so you can never be sure that you have captured all  
> > the inputs to the perceptual function that produces your target  
> > perception.
> > 
> > ```
> > All three problems are worse in the wild than in the lab, but
> > 
> > ```
> > 
> > there’s really nothing you can do about that. In the lab you can do  
> > what psychologists have been doing for a century or more – either  
> > deliberately increase contextual variability in a random way or try  
> > to keep the context as stable and as bland as you can. The first  
> > increases the noise, but gives you much more confidence you are  
> > right if you get a clear answer, while the second increases the  
> > likelihood you will get a clear answer, at the cost of lost  
> > generalizability.
> > 
> > ```
> > Despite these issues, the TCV can still be useful as a guide, and as
> > 
> > ```
> > 
> > an analogy of what we do when interacting with other people. So  
> > let’s look at the steps that follow the preliminaries, first for  
> > Yes-No ("is this particular environmental variable perceived by a  
> > perception that is being controlled?).
> > 
> > ```
> > 3(YN). Find some action that you are sure will influence V if it is
> > 
> > ```
> > 
> > not being controlled. If you can estimate the magnitude of the  
> > effect your influence should have on V in the absence of control, so  
> > much the better. If not, and you can measure both the magnitude of  
> > your influence as you randomly change it and the magnitudes of the  
> > variable and if possible the supposed influence of the controller on  
> > V, you are still in good shape, because:
> > 
> > ```
> > 4(YN)a If you apply your influence abruptly, and the value of V
> > 
> > ```
> > 
> > changes rapidly but then tends to return toward its previous value,  
> > then V is related to a controlled perception. It is controlled. If  
> > it returns toward it earlier value only after you remove your  
> > influence, or does not return at all, it is not controlled.
> > 
> > ```
> > 4(YN)b If the effect of your influence on V is less than expected,
> > 
> > ```
> > 
> > or if the effect of your influence is larger when you prevent the  
> > supposed controller either from perceiving the magnitude of V or  
> > from influencing it, then V is an environmental variable related to  
> > a controlled perception. It is controlled.
> > 
> > ```
> > 4(YN)c If your randomly varying influence magnitude changes have a
> > 
> > ```
> > 
> > high correlation with the changes in the magnitude of V, and a low  
> > correlation with the influence of the supposed controller, V is not  
> > controlled. If your influence is highly negatively correlated with  
> > the influence of the supposed controller and only slightly  
> > correlated with V, then V is related to a controlled perception, and  
> > is controlled.
> > 
> > ```
> > In the YN situation, you don't care whether V actually is the
> > 
> > ```
> > 
> > variable perceived by the perception that is controlled. To say that  
> > V is controlled is simply to say that its variation under  
> > disturbances is countered to some extent by the actions of the  
> > controller. That will be the case for say, V = X + Y + Z if the  
> > controlled perception is of X + Y and the other variable, Z, changes  
> > only slightly compared to the variation in X and Y. But if that’s  
> > all you want to know, YN is your way to go.
> > 
> > ```
> > The categorical (FC) situation is easier. Your question is which of
> > 
> > ```
> > 
> > a defined list of environmental variables corresponds to a  
> > controlled perception. Implicitly you are asserting that exactly one  
> > of the list is correct.
> > 
> > ```
> > 3(FC) Arrange to disturb all of the hypothesized environmental
> > 
> > ```
> > 
> > correlates of controlled perceptions with a randomly varying  
> > influence that may be the same for all or may be individualized. If  
> > you are correct that one and only one is the environmental variable  
> > corresponding to a controlled perception, then all but the correct  
> > one will vary in a way highly correlated with the changes in your  
> > influence while the correct one will have a low correlation with  
> > your influence.
> > 
> > ```
> > In the unforced choice condition (UC), you add the possibility "none
> > 
> > ```
> > 
> > of the above". If that is the correct answer, then all of the  
> > hypothesized environmental correlates will have a high correlation  
> > with your influence.
> > 
> > ```
> > Finally you have the continuous variants of FC and UFC. Here, the
> > 
> > ```
> > 
> > form of the hypothesised controlled perception is assumed, but you  
> > don’t know what environmental variable parameter values correspond  
> > to it. Is it X+Y, 1.2X+0.8Y or something with a ratio between those  
> > possibilities? In this case, you only have to disturb X and Y with  
> > independent random variations of your influence on them, and find  
> > the X/Y ratio of disturbance scale that gives the lowest correlation  
> > between the disturbance and the environmental variable.
> > 
> > ```
> > I don't know if these steps are sufficient for your purposes, but
> > 
> > ```
> > 
> > they might serve as a guide. Ask what it is you want to achieve, ask  
> > how your current state differs from that, and ask whether the TCV is  
> > the right tool to allow you to achieve what you want – or at least  
> > get closer than you are – and if so, which form of the TCV is  
> > appropriate.
> > 
> > ```
> > Martin
> > 
> > ```

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