- [Instructor] Most of us have heard of double-blind studies
but most data scientists don't work in a setting,
or an industry where they get an opportunity to conduct them
A more complete name is a randomized
double-blind placebo control study.
They are often described with phrases
like "the best method," or "the gold standard,"
or "least likely to be biased,"
or "the most convincing."
That can inspire feelings of frustration
because many of us are competing with the reputation
of a technique that is not available to us.
We'll discuss alternatives in this course,
so we will have options but let's first,
get clear about what the features are,
and why they are considered so attractive.
What makes it a double-blind?
In a double blind-study, not only the patient
but also the clinician is unaware of the assignment.
The assignment being whether or not
the patient was given the treatment, or the placebo.
Without blinding the patient's beliefs
in the efficacy could impact the results.
The purpose of double blinding is that the clinician
could accidentally give subtle clues during the treatment.
There's even something called triple blinding
where even the data analysts, and researchers
don't know which group is which.
So let's recap with a list of these characteristics.
There's a placebo group, there's randomization,
it's prospective meaning that assignment to treatment,
or a placebo is done before the study begins.
And finally, as we've discussed, there is blinding.
These characteristics work together
to produce the type of study that most scientists,
and statisticians find the most convincing.