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Re: Fw: Iowa Controls - Not Matched
Dr. Long,
I don't mind having a scientific discussion with you via direct email, but
your tone is harassing and your postings are not logical. I have no idea
who half these people are your copying these emails to. I wonder if in fact
they share your views? You claim you are an epidemiologist, but your
responses lack any scientific rigor or even a basic understanding of
epidemiologic methods. To think that we choose Iowa because of any of
Cohen's work is ludicrous. The people who wrote the first grant proposal
for the Iowa study in the early 1990s were not even aware of Dr. Cohen's
work. I have already answered your other questions concerning why we
choose Iowa and the possibility of having matched cases and controls by
smoking status. As I stated directly to you many times before, if you think
there are problems with the Iowa Radon Lung Cancer Study use the scientific
method and write a letter-to-the-editor. At this point, I see no
constructive reason to continue discussions with you.
Bill Field
----- Original Message -----
From: <hflong@postoffice.pacbell.net>
To: field <bill-field@uiowa.edu>
Cc: <hflong@pacbell.net>; <rosalyn@ioip.com>;
<michael.g.stabin@vanderbilt.edu>; <blc+@pitt.edu>; <rcihak@techline.com>
Sent: Friday, January 11, 2002 7:33 PM
Subject: Re: Fw: Iowa Controls - Not Matched
> Hormesis Defenders,
> Field, representative of authoritarian teaching, seems hopeless.
>
> 1. Location. Field ignores the fact that, whether intentional or not,
selecting
> Iowa, the 1% outlier location not refuting LNT, determines outcome as
surely as
> selecting the one drug study in 20 that, by chance, will show benefit.
> 2.Timing. Field obviously does believe, "We conducted a superior study,
> independent of Cohen's design or results" - but he did it after Iowa was
known
> to be atypical and perhaps fit LNT.
> 3. Biased controls. "The model included continuous variables for ---". He
> trusted calculations, using "controls" smoking 32% when cases smoked 86%!
Why do
> we bother with double blind, placebo-controlled studies? Why not
statistically
> "adjust"?
>
> I would not be alive today, if I had trusted calculations for the
foot-launched
> flying wing I flight-tested. The test pilots' guideline is, "Design is
nothing,
> construction is nothing, TESTING is everything."
> I would have been unable to pull out of a dive (because air pressure
deactivated
> a too-flexible stabilizer). Field seems unable to pull out of a dive
because of
> pessures and too flexible a scientific stabilizer.
>
> Next? How about a column, Robert? How about exploring SF General Hospital
HIV +
> outpatients already having T testing, Myron and John?
>
> Howard Long
>
> field wrote:
>
> > Dr. Long.
> >
> > > >
> > > > Howard Long MD MPH, Family Doctor and Epidemiologist
> > > > 363 St. Mary St., Pleasanton CA, 94566
> > > > (925) 846-4411, Fax 4524, Page 787-0253 hflong@pacbell.net
> > > >
> > > > Dear Professor Field,
> > > >
> > > > I have great respect for your scientific honor and the quality of
the
> > > > Iowa study.
> > > > I am happy that you write, "I AM NOT A DEFENDER OF THE LNT THEORY".
> > > >
> > > > When opposite inferences are reasonable from similar studies,
> > > > like your
> > > > Iowa study and the N Shipyard Worker Study (also case control and 10
x
> > > > as large as yours), I believe an experiment is needed.
> > > >
> > > > First, even if a drug company were to fund 100 clinical trials,
> > > > (prospective and double blind) with N in each such that some trials
> > > > would likely show p<.05 of chance results,but publish only studies
> > > > showing benefit, would it show the medicine effective?
> > > > You studied the one location in 100 (Iowa women) having no negative
> > > > correlation of radon and lung cancer mortality, in Cohen's
> > > > study - 200 x
> > > > as large, albeit ecologic.
> > >
> > > I trust that he is not suggesting that we chose to do our study in
Iowa
> > > because this was one of the states in the 50 or so in Cohen's study
that
> > had
> > > a positive association. The study was funded and done in Iowa because
> > Iowa
> > > is the ideal state to do such a study. Perhaps, this later reason is
why
> > a
> > > positive association has been observed in Iowa.
> > >
> > > The main argument against Cohen's studies is and always has been this:
> > > aggregation in an ecologic study can lead to biased estimates. The
bias
> > can
> > > be so bad as to yield estimates with the wrong sign, as Jay Lubin has
> > shown.
> > > Increasing the sample size does not reduce the bias in any way; it
simply
> > > leads to more precise estimates. In other words, you would be more
> > > precisely estimating the wrong thing.
> > >
> > > I don't understand the analogy. It only makes sense if we purposely
> > picked
> > > Iowa because it happened to have the change association, and we
reported
> > > Cohen's findings for Iowa. Neither case is true. We conducted a
superior
> > > study independent of Cohen's design or results. Whether our findings
> > agree
> > > with the hypotheses generated in Cohen's ecologic study is irrelevant
to
> > me.
> > > I am intimately aware of how the data was collected and analyzed in
both
> > > studies. The results from Cohen's ecologic study are dubious because
of
> > the
> > > increased risk of biases inherent in his study design. Larger sample
> > sizes
> > > can not overcome bias (a clear case of quality versus quantity).
> > >
> > > > .
> > > > Second, in Topics Under Debate, Radiation Protection
> > > > Dosimetry V95,1,p77
> > > > you write in Rebuttal, "The participants' smoking histories
> > > > do not need
> > > > to match the smoking histories of the controls since the effect of
> > > > smoking can be adjusted for using standard statistical methods."
This
> > > > follows Klaus Becker's Argument that "- in the Iowa Lung
> > > > Cancer Study by
> > > > Field et al 86% of the ling cancer cases were smokers, but only 32%
of
> > > > the controls." Ibid, p79. Our Professor of statistics at UCB PH,
Bill
> > > > Gaffney, would often remind us,
> > > > "Know your assumptions!" In your study, the controls are not
> > > > matched. I
> > > > do not believe that here, "smoking can be adjusted for using
standard
> > > > statistical methods".
> > >
> > > Multiple logistic regression was used to model the effect of
residential
> > > radon exposure on lung cancer risk. Included in the regression model
were
> > > variables to adjust for the effects of smoking. Specifically, the
model
> > > included continuous variables for the length of time that individuals
> > > smoked, the number of cigarettes smoked during that time, and time
since
> > > smoking cessation (for ex-smokers).
> > >
> > > Quoting Hosmer and Lemeshow's authoritative book, "Applied Logistic
> > > Regression":
> > >
> > > "One generally considers a multivariate analysis for a more
comprehensive
> > > modeling of the data. One goal of such an analysis is to
statistically
> > > adjust the estimated effects of each variable in the model for
differences
> > > in the DISTRIBUTION of and associations among the other independent
> > > variables. Applying this concept to a multivariate logistic
regression
> > > model, we may surmise that each estimated coefficient provides an
estimate
> > > of the log odds [of lung cancer] adjusting for all other variables
> > [smoking]
> > > included in the model."
> > >
> > > I would further suggest that there is no practical way to match cases
and
> > > controls so as to adjust for the effects of smoking on lung cancer
risk.
> > > Smoking is so strongly and intricately associated with lung cancer
that
> > one
> > > would have to match on a multitude of factors, including intensity,
> > > duration, and time since cessation. Furthermore, there would
undoubtedly
> > be
> > > other covariates such as age, education, second hand smoke, family
> > history,
> > > and occupational exposures that would not be matched and would have to
be
> > > controlled for in some fashion; i.e. multiple logistic regression.
> > >
> > > >
> > > > I, unlike some cynical colleagues, believe that your intent,
> > > > like mine,
> > > > is to prevent lung cancer and advance science. I have in the past
> > > > rationalized projects (like a method of colon cancer detection) more
> > > > than I believe you have rationalized this power of statistics
> > > > to correct
> > > > for the difficulty in finding controls that match for smoking. I
hope
> > > > you will come to believe, as I do, that less smoking by controls may
> > > > have been the reason they had less cancer, rather than the less
radon.
> > > >
> > > > With continued respect and best wishes
> > > >
> > > > Howard Long
> > > >