[From Bill Powers (951125.1605 MST)]
Bruce Abbott (951125.1510 EST) --
An "independent variable" is not a variable that "assumes an
arbitrary value with no relationship to anything else." It is a
variable whose value (state) is manipulated by the experimenter.
Independent variables exist whenever an experimenter manipulates a
variable.
Precisely the point I made later in the post:
The very concept of an experimentally-manipulated independent
variable, therefore, implies a control system in the background, a
system which can act to make a perceived pattern of change match a
reference pattern.
But my point seems to have escaped you:
I am unclear about this distinction you make here. If an
independent variable is being manipulated for experimental
purposes, it cannot be changing naturally, as then one would not
have an experiment but only a type of correlational design.
An environmental variable might change because other variables in the
environment change. The illumination in a cage might change because the
sun shines in the window. Or it might change in a way planned by an
experimenter, who adjusts the pattern of light and dark -- say, on a 27-
hour schedule. The first change is natural, and would be affected by the
season, by cloudiness, and by the state of the windowshades. The second
is under control by the experimenter, following a predetermined pattern.
There is no other essential differencd.
Controlled variables have the property that their values follow the
value of a reference signal inside the controlling system. Normally, the
physical variables under control would depend on other environmental
influences. Those influences, although still present, are counteracted
by the action of the controlling system, so the variable follows the
arbitrary changes in reference signal -- i.e., the pattern the
experimenter wants to see instead of the natural one. This is what we
mean by "manipulating" a variable -- sometimes, literally "manually"
changing it in a predetermined way.
Now let us try a different experiment. I deliver a shock through
the grid floor of an operant chamber and the rat runs in a circle
around the chamber so long as the shock continues. Shock, the
independent variable, appears to be a cause of running, the
dependent variable. Taking a cue from physics, I then force the
rat to run (perhaps by reinforcing running behavior through
successive approximation). To my surprise, the rat's running
generates no measurable current in the grid. The reason, of
course, is that running and shock-level are not mutually-
influencing variables.
Yes, but you're misidentifying the system in this case. The rat's
running is affecting the experienced shock, over time. The rat runs not
because of a single shock, but because of an effect experienced over
many instances of shock, and it runs because the running has an effect
on the experience. The experience of importance, therefore, is the joint
effect of administration of shocks and running, not the shocks alone or
the running alone. There is a relationship involving administered
shocks, running, and the experiences arising from shock.
The electric current is also a controlled variable. The experimenter
varies the schedule and strength of shock until some satisfactory
pattern of running is seen. So the administration of shock is the
experimenter's output, and the perceived pattern of running is the
controlled variable. If the rat does not run, the schedule is adjusted
or the strength of the current is raised until it does run. If it runs
too much -- continuously, or in some undesired pattern -- the
administration of shocks is against adjusted until the desired pattern
is seen (or the desired range of patterns). So the shocks affect the
running, and the running affects the shocks, when the entire
experimenter-animal system is considered.
But this does not appear to be the case in the rat experiment, does
it? The rat's action appears to be a function of shock-level, but
shock-level does not appear to be a function of the rat's action.
Certain relationships cannot be described as a set of variables in
simultaneous equilibrium, in which a forced change in any one
variable is accompanied by instantaneous changes in the others.
When such mutual relationships do exist, one can literally _define_
any one variable in terms of the others, as when E = I/R, or I =
ER, or R = I/E. But not all relationships involve mutual
causality.
This is true: not all relationships involve mutual causality. In most
physical situations, there is an action-reaction equilibrium. But when
we deal with living systems, there are processes in which the input-
output relationship is strong, while the reverse relationship is
essentially missing. This can occur only when there is power
amplification. If living systems were open-loop systems, we would have
this relationship:
(power loss) (power gain)
manipulated variable --> proximal stimulus --> organism --> response.
(turn on shock) (effects of shock) (running)
When you manipulate a variable and observe the final effect in a chain
like this, you are actually observing a one-way causal chain. This kind
of chain almost never appears naturally in non-living systems, although
there are examples. A conventional causal interpretation would be
appropriate if the system in question is actually organized as above.
However, the PCT claim is that living systems are organized like this:
(power loss) (power gain)
manipulated variable --> proximal stimulus --> organism --> response.
^ |
···
(feedback effect) |
----------------------------
(turn on shock) (effects of shock) (running)
This means that the response affects the proximal stimulus and the
proximal stimulus affect the response. In this loop, there is no simple
causation. The manipulated variable tends to alter the proximal
stimulus, but the proximal stimulus is also altered by the response,
with the result that the proximal stimulus tends to remain near a level
preferred by the organism.
In the case of the rat and the shock, there is no feedback effect fast
enough to counteract a single shock. But the "proximal stimulus" in this
case is not the effect of a single shock. It is an effect averaged over
time. The running can vary in such a way as to counteract (to some
extent) this average effect, so it is the average effect that is part of
the loop. The only reason there is running is that it does have an
influence on this average effect; if it had no influence at all -- if
running or not running made no difference in what the rat experienced --
there would be no running. That is the main thesis of PCT: the ONLY
reason for behavior is to control perception.
Yet no manipulation of any of these variables will change either r
or d, although changing either of the latter will force a
simultaneous change in p, e, o, and i as they approach new
equilibrium values. A set of simple experiments designed to
identify the causal relationships would show that both r and d
affect p, e, o, and i, that changes in r do not affect p, and
changes in p do not affect r.
This is true, and both r and d have been identified in PCT as true
independent variables (relative to the loop). But they are causal only
in a _joint_ manner; neither one alone is a cause of any unique
behavior. And the effect is an effect on the entire loop, not just one
variable in it such as o.
I strongly disagree that so-called "IV-DV" methods are at fault.
As noted, one can use such methods to identify which variables
influence which, whether the variables in question participate in
an open-loop or closed-loop relationship. We can agree that it
would be preferable to refer to such relationships as cases of
simultaneous influence (either one-way or two-way) rather than as
cases of "cause and effect," as the latter implies a time-order
that may not be appropriate. However you refer to them, "IV-DV
methods" can reveal such influences, of either type.
There is nothing wrong with IV-DV in itself: it's simply a method of
dealing with apparent causality. But I emphasize the "apparent." One can
get entirely the wrong impression of how a system works by using the IV-
DV approach naively. This is the main point that PCTers have been trying
to make. It's not that manipulated variables don't result in changes of
response: they do. But WHY they do makes all the difference. If you just
take appearances at face value, you will never discover that there is
that "proximal stimulus" in the diagrams above that actually forms a
_barrier_ to most of the effect of the "independent variable," since the
response blocks the passage of most of the effect of the IV into the
organism. Furthermore, the response brings the proximal stimulus to the
level that the organism wants rather than to the level that would
normally be created by the independent variable (in the absence of an
active response). Instead of the IV controlling the state of the
proximal stimulus, the organism controls it.
In your vocabulary of present-time relationship, do you distinguish
relationships in which there exists a direct influence of one
variable upon another (or even mutual influences) from
relationships in which two variables change together over time, not
because they directly influence each other, but because each is
responding to the influence of the same third variable? In the
traditional vocabulary one would say that the former relationship
is causal whereas the latter is only correlational. If you do make
this distinction, what terms convey it? It seems to me that the
term "causal" has continued to enjoy acceptance in psychology
precisely because it so nicely conveys this distinction.
In a system analysis, where component input-output relationships are
expressed mathematically and then the whole system of equations is
solved, there is no need for this artificial distinction. All such
distinctions fall out of the solution.
You have made the valid point that there are, indeed, one-way causal
relations in nature. They are seen whenever you draw a boundary around
some part of the environment to create inputs and outputs. Whether you
intended to or not, you also pointed out that there are one-way
relationships which depend on power amplification, and these, piecewise,
are also true cause-effect relationships. In such cases, IV-DV analysis
is entirely appropriate. But by the same token, IV-DV can give a false
impression of what is going on between input and output -- it can give
the impression that there is a simple causal chain connecting input to
output, when in fact the interior of the system can be organized in ways
that are not describable that way -- a control organization being one,
but not the only one.
As to cause-effect and IV-DV not being the same thing, I'm not sure what
you mean. Explain again, please.
-----------------------------------------------------------------------
Best,
Bill P.