Just a few points:

(1) I guess that before going to bed folks should read Campbell
and Stanley and/or Cook and Campbell and/or Shadish's updating
of their material because the issues raised by Mike Williams fall 
under the topic of "threats to internal validity".  Specifically,
(a) diffusion or imitation of treatments and (b) compensatory 
rivalry or resentful demoralization.  In both of these situations, 
knowledge of the different treatments used in a between-subjects 
design, can affect how subjects respond or fail to respond to 
treatments.  It should be noted that drug treatment studies can be 
conducted with within-subject designs such as crossover designs 
where one group receives a drug treatment first and, after a 
washout period, receives a placebo treatment.  Another group 
has placebo first and drug later.  In any event, a competent researcher 
will make sure that the design they use addresses threats to the 
different types of validity involved in the study and try to make 
sure that their effect is negated or minimized.  Here is link to 
Pedhazur & Schmelkin's treatment of validity issues in their text 
"Measurement, Design, and Analysis":
http://tinyurl.com/PedhazurIntValid 

(2)  It might be a somewhat useful to follow the research heuristic
that "all treatment/medication studies involving human are invalid"
but, as with all heuristics, there will be situations where it fails and 
situations where it is right but for the wrong reasons.  In the example 
that Williams uses below, it is clear that in an inpatient/ward study, 
one has to guard against the threats I identify above. But if one uses 
an outpatient population where the participants have no contact 
with each other, it is hard to see the merit in Williams' critique.  
There are many different ways to conduct a drug/treatment/intervention 
study and the quality of that research is dependent upon what the 
person in charge knows about research design, the different types 
of validities involved as well as threats to them, and the degree of 
control one has over the research situation.

(3) A minor point:  I would assert that though one's own personal
experience is, perhaps, a useful guide to think about things, it does
not necessarily constitute a valid guide.  It is helpful to remember
that "anecdotes do not constitute data" (unless, of course, one is
doing a qualitative study where subject's statements are the data).
Williams does not provide the results of the study he was involved
which is odd because he suggests that the study should have produced
statistically significant results.  If the study did, the logical follow-up
question would be was the effect obtained with other types of designs
(e.g., out patient studies where subjects did not have contact with
each other).  The objection that Williams makes is limited to a
particular research situation and does not hold for other designs
where the threats are not relevant.  This one point invalidates
the "universality" of his claims that all drug studies are all invalid.

(4)  I have conducted the statistical analysis for a few drug studies
as represented in the following publications:
(a) The effectiveness of antianxiety medications (after participating 
receiving a sodium lactate infusion to see if it provoked a panic attack):
http://tinyurl.com/Liebowitz1984 
(b)  Whether fenfluramine positively affects behavior and attention
in young children with autism:
http://www.springerlink.com/content/t152543684578671/
(c)  The use of bromocriptine in the treatment of cocaine addiction:
http://onlinelibrary.wiley.com/doi/10.1111/j.1521-0391.1997.tb00392.x/abstract
One of the things that one learns from analyzing the data from such studies
is that subjects can have very different responses to treatment, sometimes
contrary to what "commonsense" would lead one to expect, such as
finding that the placebo condition has MORE side effects than the
drug condition.  One should also keep in mind that though one can
engage in a "guessing game" about which treatment one is receiving,
people are not 100% accurate in making such predictions and there
probably are drugs where the effects are not perceptible or the
effects build up slowly over time and the day to day changes are
not noticeable (think of the frog in pot on the stove where the heat
is low but eventually comes to a boil).

In summary, many research studies are flawed, some fatally flawed
and useless while the flaws in others are not fatal.  One can always
check the systematic reviews on the Cochrane Collaboration website
(www.cochrane.org ) to see how many crappy treatment/intervention
studies have been published because the researchers did not address
the different types of threats to the validity of the study.  Trying to
claim that all studies are invalid or all studies are valid is logically
invalid from an inductive perspective -- it is as foolish as claiming
that "All swans are white".  Those without experience with black
swans will swear the "all swans are white" if that has been their
lifelong experience.

-Mike Palij
New York University
[email protected]



------------------ Original Messages ------------------------------
On Mon, 12 Sep 2011 23:24:29 -0700, Mike Williams wrote:
Hello All.

When I was a grad student, we were conducting a clinical trial of Imipramine vs 
Xanex in the treatment of severe depression.  The study was
conducted on an inpatient research unit in the hospital.  The patients lived 
there and I noticed that they would sit in the day room in
the evenings and discuss their treatment.  Although the medications were 
assigned randomly and the researchers did not know the assignment,
the patients with dry mouth and constipation knew they were taking the 
medications.  Those given placebo knew this because they did not suffer
constipation and dry mouth (the anticholinergic side effects).  The patients 
knew which treatment they were receiving and they communicated
this to the investigators because the investigators constantly monitored the 
side effects.  The constant monitoring of side effects
unblinds the study.

This happens in every clinical trial of psychotropic medications.

This problem is even more obvious in every clinical trial of psychotherapy.  
All these studies are invalid.

I could explain why they are invalidated by referring to the gigantic 
literature on expectation biases.

Since all the dependent measures involve a judgement by the patient or the 
investigator that the disorder got better or worse, they are
all influenced by the expectation bias that the treatment worked.  I think many 
subjects want to help the researchers and they endorse
small positive changes on the dependent measures.  The people who get placebo 
behave consistent with this because they know they never
got treatment.

All the investigators have to do is anonymously survey the subjects.  The 
results will blow their minds.  To my knowledge, this obvious,
simple assessment has never been made.

Now you may be able to understand why the treatment effect size today for 
antidepressants is the same as the placebo effect for some
studies in the past - its all noise.

Mike Williams

______________________________________________________

Hi Mike:

This is a very interesting point but I am not sure that I follow
the argument completely.  Please expand your argument, dotting
the 'i's and crossing the 't's.

Ken

On 9/12/2011 3:00 AM, Mike Wiliams wrote:


Clinical Psychology psychotherapy and psychotropic medication
therapies will never have sufficient empirical support simply
because the
subjects are never blind to the treatment condition.

*************************
All the


investigators are doing is training the subjects to endorse
change on the
dependent measures.

**************************
That's why the meta-analyses conclude that


any therapy is effective. I have never seen an analysis that
addressed this research problem. It's similar to the obesity
researchers who never notice that their entire field is based on
the dieting behavior of young women.



Mike Williams
Drexel University



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