1.4 Experimental Design and Ethics
Randomized Experiments
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments. Proper study design ensures the production of reliable, accurate data.
An observational study is a study based on observations or measurements. When an apparent association between two factors/variables is observed, we still can’t conclude that one variable is the cause of the effect observed. For example, we’ve all heard this saying, “an apple a day, keeps the doctor away.” And, we’ve never seen uncle Joe sick. Does that mean the apple is the cause for uncle Joe’s good health? Or could there be other factors we’re not paying attention to at the moment that could be lurking in the background?
Association vs. Causation
Confounding/lurking variables are other potential variables that could have caused the same outcome and it is not possible to determine which factor actually caused the result. When one variable causes change in another, we call the first variable the explanatory variable. The affected variable is called the response variable.
In order to prove that the explanatory variable is causing a change in the response variable, it is necessary to isolate the explanatory variable. The purpose of an experiment is to investigate the relationship between two variables. In a randomized experiment, the researcher manipulates values of the explanatory variable (treatments) and measures the resulting changes in the response variable. Experiments are designed in such a way that there is only one difference between groups being compared: the planned treatments. This is accomplished by the random assignment of experimental units (object or individual to be measured) to different treatment groups, typically a control group and a treatment group. The treatment group receives the treatment being tested; the control group does not receive the treatment but instead receives a placebo (fake treatment). When subjects are assigned treatments randomly, all of the potential lurking variables are spread equally among the groups. At this point the only difference between groups is the one imposed by the researcher — the treatments. Different outcomes measured in the response variable, therefore, must be a direct result of the different treatments. In this way, an experiment can prove a cause-and-effect connection between the explanatory and response variables.
The Placebo Effect
Is it Real?
Randomization in Clinical Trials
Clinical Trials/Experiments
In a blind study, the participants do not know whether they’re receiving the treatment or the placebo. In a double-blind study, all participants in the study, including the researcher and subjects, are not informed which subjects are in the treatment group and in the control group. Learn more about Experimental Design.
Ethics
When a statistical study uses human participants, as in medical studies, both ethics and the law dictate that researchers should be mindful of the safety of their research subjects. The U.S. Department of Health and Human Services oversees federal regulations of research studies with the aim of protecting participants. When a university or other research institution engages in research, it must ensure the safety of all human subjects. For this reason, research institutions establish oversight committees known as Institutional Review Boards (IRB). All planned studies must be approved in advance by the IRB. Key protections that are mandated by law include the following:
- Risks to participants must be minimized and reasonable with respect to projected benefits.
- Participants must give informed consent. This means that the risks of participation must be clearly explained to the subjects of the study. Subjects must consent in writing, and researchers are required to keep documentation of their consent.
- Data collected from individuals must be guarded carefully to protect their privacy.
It is important that students of statistics take time to consider the ethical questions that arise in statistical studies. How prevalent is fraud in statistical studies? You might be surprised—and disappointed. There is a website dedicated to cataloging retractions of study articles that have been proven fraudulent. A quick glance will show that the misuse of statistics is a bigger problem than most people realize.
PRACTICE
