Insights of Confounding

Confounding

Based on the “Multicausality: Confounding – Assignment,” by Schoenbach, discuss two
significant insights you learned about confounding. Use specific examples from the
assignment to support your answer.

Insights of Confounding

Experimental sciences are part of the ideas of confounding meant to minimize
unnecessary variability through a process where the relevant factors are controlled through
experimental design. The ability to generate reproducible findings during experiments is a factor
of the various control opportunities indicated for experimental sciences. Control groups are
utilized in empirical sciences to help introduce some control in those sources of variability which
the experimenter cannot manipulate. Comparing both experimental and control findings makes it
possible for the researcher to understand certain conditions typical for unwanted influences. Use
of control groups helps to identify awkward results during an experiment, which might lead to
misleading conclusions (Recalt & Cohen, 2019). The control groups give the experimenter an
idea of what to expect following an experiment to make sure that the findings produced are
reasonable.
Randomized trials are another insight of confounding, which is used in epidemiological
studies alongside experimental models. Randomized trials are used in cases where a large study
group is involved in reducing the amount of time and resources needed to generate the required
findings. The experimenter selects the qualifying samples or participants at random and uses
them to produce results that are representative of the entire study group. In a large study
population, small groups are created from which the participants are selected at random to be

CONFOUNDING 2
used in the intended study (Deaton & Cartwright, 2018). The fact that participants are picked
without a defined criterion, the process results in cases where the findings might not describe the
characteristics or attributes of the entire group fully. In such a trial, the experimenter aims at
producing findings that are of high accuracy for them to be scientifically approved.

References

Deaton, A., & Cartwright, N. (2018). Understanding and misunderstanding randomized
controlled trials. Social Science & Medicine, 210, 2-21.
Recalt, A. M., & Cohen, D. (2019). Withdrawal confounding in randomized controlled trials of
antipsychotic, antidepressant, and stimulant drugs, 2000–2017. Psychotherapy and
Psychosomatics, 1-9.

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