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In statistics, an
observational study draws inferences about the
possible effect of a treatment on subjects, where the assignment of
subjects into a treated group versus a control group is
outside the control of the investigator.
This is in contrast with controlled
experiments, such as randomized controlled
trials, where each subject is randomly assigned to a treated
group or a control group before the start of the treatment.
The assignment of treatments may be beyond the control of the
investigator for a variety of reasons:
- A randomized experiment would violate ethical standards. Suppose one wanted to
investigate the abortion–breast cancer
hypothesis, which postulates a causal link between induced
abortion and the incidence of breast cancer. In a hypothetical
controlled experiment, one would start with a large subject pool of
pregnant women and divide them randomly into a treatment group
(receiving induced abortions) and a control group (bearing
children), and then conduct regular cancer screenings for women
from both groups. Needless to say, such an experiment would run
counter to common ethical principles. (It would also suffer from
various confounds and sources of bias, e.g., it would be impossible
to conduct it as a blind experiment.) The published
studies investigating the abortion–breast cancer hypothesis
generally start with a group of women who already have received
abortions. Membership in this "treated" group is not controlled by
the investigator: the group is formed after the "treatment" has
- The investigator may simply lack the requisite influence.
Suppose a scientist wants to study the public health effects of a
community-wide ban on smoking in public indoor areas. In a
controlled experiment, the investigator would randomly pick a set
of communities to be in the treatment group. However, it is
typically up to each community and/or its legislature to enact a
smoking ban. The investigator can be expected to lack the political
power to cause precisely those communities in the randomly selected
treatment group to pass a smoking ban. In an observational study,
the investigator would typically start with a treatment group
consisting of those communities where a smoking ban is already in
- A randomized experiment may be impractical. Suppose a
researcher wants to study the suspected link between a certain
medication and a very rare group of symptoms arising as a side
effect. Setting aside any ethical considerations, a randomized
experiment would be impractical because of the rarity of the
effect. There may not be a subject pool large enough for the
symptoms to be observed in at least one treated subject. An
observational study would typically start with a group of
symptomatic subjects and work backwards to find those who were
given the medication and later developed the symptoms. Thus a
subset of the treated group was determined based on the presence of
symptoms, instead of by random assignment.
In all of those cases, if a randomized experiment cannot be
carried out, the alternative line of investigation suffers from the
problem that the decision of which subjects receive the treatment
is not entirely random and thus is a potential source of bias. A major challenge in conducting
observational studies is to draw inferences that are acceptably
free from influences by overt biases, as well as to assess the
influence of potential hidden biases.
An observer of an uncontrolled experiment (or process) records
potential factors and the data output: the goal is to determine the
effects of the factors. Sometimes the recorded factors may not be
directly causing the differences in the output. There may be more
important factors which were not recorded but are, in fact, causal.
Also, recorded or unrecorded factors may be correlated which may
yield incorrect conclusions. Finally, as the number of recorded
factors increases, the likelihood increases that at least one of
the recorded factors will be highly correlated with the data output
simply by chance.
In observational studies, investigators may use propensity
score matching (PSM) in order to reduce overt biases.
In 2007, several prominent medical researchers issued the
Strengthening the Reporting of Observational Studies in
Epidemiology (STROBE) statement, in which they called for
observational studies to conform to 22 criteria that would make
their conclusions easier to understand and generalise.
- ^ "Observational
study". http://www.medicine.ox.ac.uk/bandolier/booth/glossary/observ.html. Retrieved
von Elm E, Altman DG, Egger M,
Pocock SJ, Gøtzsche PC, Vandenbroucke JP (2007).
"The Strengthening the
Reporting of Observational Studies in Epidemiology (STROBE)
Statement: Guidelines for Reporting Observational Studies".
PLoS Med. 4 (10): e296. doi:10.1371/journal.pmed.0040296. PMID 17941714. http://medicine.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pmed.0040296&ct=1.