00:01
that I've got that straight in your mind,
let's think about the quasi-experiment again.
00:05
The quasi-experiment resembles an RCT, but
lacks randomization. Do you remember why we
randomized? We randomized to control for extraneous
variables, especially the ones we don't know
about. So we control for confounding more
than anything else. Before we can control
for that, quasi-experiments lack internal validity,
or at least internal validity is in jeopardy.
00:28
Keep that in mind. Why do we use it then?
Well sometimes randomization is not possible,
in the example we worked through with the
broadcast of the radio documentary on boiling
water, you can't randomize that sort of thing.
I also cannot control for blinding because
people know whether or not they heard a radio
broadcast. On the other hand, because it takes
place in the real world, it's in a real community
where people live and work and they are listening
to the radio broadcast and applying it in
their real lives automatically. Automatically
it has external validity, so we've compromised
internal validity, but we've gained a lot
of external validity.
01:08
Now let's talk about something called a natural
experiment. Something that is quite close
to my heart because while I finished my doctorate
my very first job interview involved someone
asking me about a natural experiment. The
job interview was for a position in radiation
epidemiology, something that we don't have
a lot of data about, especially not about
large-scale doses of radiation on the population
and my interviewer asked me, "Can you think
of a natural experiment from which we can
derive data to measure radiation and health?"
And I blanked and I couldn't think of one,
but the answer is obvious; end of World War II,
the dropping of the atomic bombs in Hiroshima
and Nagasaki, that's a classic unfortunate
and tragic natural experiment. A natural experiment
resembles a randomized controlled trial, but
this is when the allocation of the subjects
isn't due to randomization, it is due to an
external force that the researcher had no
control over, like a natural disaster, like
a military disaster, or like a proposed law
or by-law. So this is how a natural experiment
looks. Like the rest of them, we begin with
a study population, we allocate our study
population to one or two groups, a treatment
group or a control group. The allocation though
isn't done through randomization like flipping
a coin, it is not done through choosing a
community like in a quasi-experiment, it's
done by an external factor, like a natural
disaster. So let's look at an example that's
not as depressing as the nuclear bombs in
Hiroshima and Nagasaki. Let's look at the
state of Montana where some towns decided
to pass smoking bans and we want to test whether
or not passing a smoking ban in your community
resulted in let's say, less or poor health.
So all we have to do here is find some towns
that pass the smoking ban and some towns that
didn't. Now you didn't convince them to pass
the smoking ban, someone else did. The legislature
did. An external force did it. You're now
going to reap the data rewards from that choice
however. So we find the towns that banned
smoking, some towns that did not ban the smoking
and we'll see the results from those two towns.
03:19
And again, since the researcher was not the
one to determine the allocation, this is technically
not a randomized controlled trial. It's probably
technically an observational study it can
be argued, I would say it's a kind of experiment
observational study hybrid. I want to point
out that even though I've taxonomized these
designs into observational and experimental
and so forth, it doesn't really matter which
category you think a study goes into, all
that matters is, can you interpret the results?
The naming doesn't matter; it's the interpretation
that matters.