http://spssx-discussion.165.s1.nabble.com/Correlational-Example-Involving-COVID-19-Useful-for-Classes-tp5739871p5739887.html
Just remember Sir Ronald Fisher's argument against cigarette smoking causing
multiple health problems (e.g., lung cancer, heart disease, etc.) in humans was
that all researchers have was a correlation between amount of cigarette use
and illness condition at some age (usually middle aged and older). Fisher's
justification for his explanation was that people who smoke and went on to
develop, say, lung cancer may have been genetically predisposed to have
lung cancer and, perhaps, a tendency to (enjoy) smoking.
Remember that the evidence for a causal relationship of smoking leading
to lung cancer is based on observational research because it would be
unethical to do a randomized clinical trial (RCT) like the following:
(1) Take several thousand male and females who are randomly assigned
to one of two levels: (a) starting at age 18, equal numbers of males and
femaies to a smoking condition where everyone is required to smoke one
pack of cigarettes per day for an indefinite period of time but on the order
of decades, and (b) also starting at age 18, equal numbers of males and
females are required to be tobacco abstinent and to avoid situations where
one might be exposed to second-hand smoke.
(2) At 5 to 10 year intervals all participants are given medical examinations
to screen for the presence of major diseases/illnesses. 20 years of such
data collection would probably be a minimum but it might best (if funding
can be obtained) to do up to 30 or 40 years of follow-up, at which point
mortality rates may become a more important dependent measure.
(3) Care should be taken to make sure that participants in the two groups
should have similar representation of racial/ethnic groups, SES and education
level, live in similar neighborhoods/environments, etc. Identification of other
relevant variables that might be used as covariates should be an ongoing
process, especially to better understand people who have smoked their
entire life (some into their 90s) but have not developed any significant
health conditions. This group may have a genetically based protection
against the damaging effects of smoking, something compared to people
with HIV infection for decades but do not develop AIDS -- the viral load
is kept very low by the person's immune system, suggesting that some
genetic condition bolsters the resistance to HIV developing into AIDS.
I'm sure that the above design has to be polished up before it would
be a viable undertaking but ethical considerations would probably not
permit such research from ever being done. Which is unfortunate
because this would be an experimental based procedure to establish
a causal link between cigarette smoking and health problems in HUMANS.
So, one can use observational research to address this situation (which
has been the traditional method of studying smoking in humans).
Unfortunately, there are a large number of problems with such research;
for more on this point, see:
Vandenbroucke,
J. P., Von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D.,
Pocock, S. J., ... & Strobe Initiative. (2007). Strengthening the
Reporting of Observational
Studies in Epidemiology (STROBE): explanation
and elaboration. PLoS Med, 4(10), e297.
The article can be accessed here:
A somewhat more cynical view of the medical research process is provided by
John P. A. Ioannidis in publications such as the following:
Ioannidis, J. P. (2005). Why most published research findings are false. PLoS medicine, 2(8), e124.
This article can be accessed at:
So, the contemporary medical understanding and treatment of the effects of cigarette
smoking on human health is not based on RCTs showing a causal relationship between
smoking and human health. RCTs with animals (e.g., smoking vs non-smoking dogs),
appear to support the smoking causes illness proposition but effects shown in animals
don't always transfer to humans -- the animal effect is not replicated in humans where
the effect is weak, nonexistent, or is manifested in different ways. Consequently,
the warrant to claim that cigarette smoking produces serious medical problem has to
be based on (a) observational studies with humans (but with the problem having to explain
why a number of humans do NOT develop illnesses), (b) RCT/experimental studies with
animals to show that they indeed develop serious illness as a function of time spend
smoking, and (c) bench research examining cellular and biochemical effects of the
chemicals (poisons) found in cigarette smoking, trying to determine why and which
physiological systems are being damaged.
To summarize an overlong yadda-yadda: correlations can provide information about
causation (or its absence) but one needs to know a large variety of evidence in order
to make the argument that a correlation means one thing (i.e., smoking is positively
related with the development of medical illness) and not another thing (e.g., genetic
factors that predispose one to develop illnesses [compare to the diathesis-stress
model] may also lead one to engage in smoking but plays a lesser role in the
development of an illness). Experimental designs that can be used to determine
which interpretation of the correlation relationship should be accepted cannot be
done for ethical reasons, so using info from a variety of sources that converge on an
overwhelming conclusion (i.e., smoking causes illness) is the way that the argument
has to be established.
We can leave it as an exercise to interested parties to determine which experimental
design might provide evidence that wearing a face mask reduces the number of
illness/deaths, and the willingness to wear a mask may depend upon a number of
factors, including how many people one knows that had COVID-19 and how bad
a case it was.
On an aside, the argument that people have AGAINST wearing masks reminds me
of the early part of the movie "Aliens" when Ripley is trying to convince the corporate
suits to take seriously the threat that the nearly unstoppable exeomorphs are a danger
not only on
LV-426 but to earth as well. And suits being suits, blow Ripley off. At least
until earth is not able to communicate with LV-426 and someone has to go there to find
out why. Ripley understand that if she goes there, she may be walking into a deathtrap
while the Marine and the suit Burke think they can handle anything there. Well, most
of know how that turned out. People who don't wear mask are like the marines and Burke
but have to be hit in the face with a 2x4 to realize how much danger they are in -- it's
not until their first encounter with the aliens that they realized how unprepared they are
to deal with them though Ripley's pleadings tried to get them to understand how bad
it is. Similar to the coronavirus and its resultant illness COVID-19 - until you see how
terrible it can be, one can make believe that the virus is no worse than the flu or that
it is a hoax or it's just an attempt to undermine the president. Sometimes one might
have to let a kid touch a hot pot on a stove to realize that they shouldn't touch hot
pots and pans on stoves. But some kids might need several such learning trials while
a few might turn out to be Darwin award winners. One can always give advice but
it is foolish to expect people to follow it unless they understand what is really going on.
tl;cw
-Mike Palij
New York Univerisity
P.S. It's late. Sorry about the typos and sentences that appear to suggest that
I had a temporary psychotic break with reality. ;-).
Based strictly on the data presented, one could draw the
arrow of causation in either direction.
Fauci assumes that wearing a mask prevents disease.
Trump might argue that those people who have experience
(illness in friends) realize that those mask-wearing is a result
of the panic caused by the medical profession. People "more
familiar" with the disease do not bother with masks.
For these data, interviews with persons who have switched status
(to or from mask-wearing) would be helpful for interpretation.
Herman Rubin in the stats groups offered the example of the
correlation between the number of trucks responding to a fire
alarm and the cost of the subsequent damage. More respondents
mean ("result in"?) more damage.
--
Rich Ulrich
Note: r = -0.85; the R^2 is provided in the article and I used a calculator to
get the square root and forgot to include the negative sign (as the percentage
of mask users in a state increases, the fewer one knows people with COVID-19
symptoms). Sorry about that.
-Mike Palij
New York University
---------- Forwarded message ---------
From:
Michael Palij
<[hidden email]>
Date: Fri, Oct 23, 2020 at 1:17 PM
Subject: Correlational Example Involving COVID-19 Useful for Classes
To: SPSS list <
[hidden email]>
Cc: Michael Palij <
[hidden email]>
This Washington Post article provides an interesting example of correlation
between the "percentage of people one knows with COVID-19 symptoms"
and "percent of people wearing masks in public" -- the unit of analysis is U.S.
states. There is a nice scatterplot and the data used is provided in a table
(comes from Delphi CPVODCast, Carnegie-Mellon U). The R^2 is 0.72 (r = 0.85).
I have not checked the Carnegie-Mellon source but they may be more
interesting data/analysis available there.
-Mike Palij
New York University
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