Experimental Design for the MCAT: Everything You Need to Know
/What you need to know to ace experimental design questions on the MCAT Psych/Soc section
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Part 1: Introduction to experimental design
Experimental design describes the manner in which a controlled experimental factor is subjected to a specific treatment in order to be compared with the factor that is kept constant. It is a systematic and efficient method that enables people to study the relationship between multiple factors and key responses via data collection, which eventually leads to new discoveries.
There are numerous modes of experimental design with different purposes, and it is important to understand these key differences for the MCAT exam. There are observational studies, experimental studies, and numerous ways in which studies can be designed. We will describe the major differences and aspects of each type of experimental design that you need to know.
For the MCAT, it will also be important to understand aspects of experimental design that may pose issues in validating the results of a study, such as confounding variables and different forms of bias. We’ll provide definitions of some commonly encountered forms of confounds and bias, but this list is not exhaustive.
(Suggested Reading: MCAT Psychology and Sociology: Everything You Need to Know for the MCAT)
At the end of this guide, you will also find a practice passage and standalone questions to practice applying this information to AAMC-style practice questions. Let’s get started!
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Part 2: Study deisgn
Study design refers to the sets of methods and protocols that are used to collect and analyze data in a study. These design methods are applicable to many forms of research: observational or experimental, survey-based or methods-based.
| Type of study | Description | Example |
|---|---|---|
It is also important to understand several of the key terms involved in research.
A confounding variable is a variable aside from the independent variable that influences the dependent variable. For example, suppose that there is a correlation between ice cream consumption and the murder rate within a city. The confounding variable is that ice cream consumption likely peaks during the summer months when it is hot, and more people are out and about during the summer months as well, leading to increased murder rates overall. It is therefore not increased ice cream consumption that can explain the increased murder rates, but rather the confounding variable of the summer months that may explain it.
A moderating variable affects the strength of the relationship between two variables. They can include factors such as location, gender, race, ethnicity, religion, and other demographic factors. For example, consider a study that looks into whether watching a soccer game before eating results in increased food intake. The independent variable is whether they watch the sports game, and the dependent variable is how much food they intake. The moderating variable is a factor that affects how much the independent variable affects them. So suppose that some people in the study are from Europe, and others are from Canada (also assume that there is greater interest in soccer in Europe than in Canada). This means that theoretically, someone in Europe is more interested in the soccer game and would watch it more intently than someone in Canada, so the viewing of the soccer game might have a greater impact on them and how much they eat. So the variable of nationality moderates the strength of this relationship.
A mediating variable explains why two things are related. It mediates the relationship between the independent and dependent variables. For example, consider the statement: “Whenever I exercise late at night, I feel tired the next morning.” The mediating variable in this example is that the person did not sleep enough due to exercising late at night. Therefore, not sleeping enough mediates the relationship between exercise and being tired.
The placebo effect is defined as the effect produced by a placebo drug or treatment that cannot be attributed to the properties of the placebo itself and must therefore be due to the subject’s belief that the treatment “should work”. For example, the placebo used in some drug treatments is a sugar pill that should have no measurable impact on the outcome of the patient’s condition. Therefore, if the patient feels more recovered or that their condition has been alleviated due to the placebo, this would be a placebo effect that is attributed to the patient’s belief that the treatment should help them feel better.
There are many types of validity that are important to know.
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