Study Types

Study Types

5 min read Updated Apr 19, 2026

MCAT passages live or die on study design. Every passage tells you what kind of study was run - and many questions turn on whether you can name the design. This section walks through every design you might see.

Cross-Sectional Study

Definition. Data collected from a group at a single point in time.

Example. A researcher surveys 2,000 people today and asks about their current diet and current blood pressure.

Cross-sectional studies are good for prevalence (“how common is X right now?”) and cheap to run. They are bad for causation: you cannot establish which variable came first.

Cohort Study

Definition. A group of people sharing a common characteristic (the “cohort”) is followed over time to see who develops an outcome.

Two variants based on direction in time:

  • Prospective cohort. Identify the cohort today, then follow it forward. E.g., enroll 5,000 healthy adults and measure their diet now, then track who has a heart attack over the next 20 years.
  • Retrospective cohort. Identify the cohort using records that already exist, then look at outcomes that have already happened. E.g., pull 30 years of employment records for a chemical plant, then check cancer registries.

Contrast with cross-sectional. Cohort studies follow people over time. Cross-sectional is a snapshot.

Longitudinal Study

Definition. Any study that repeatedly measures the same subjects over time.

Example. A child development study that tests the same 500 children every year from ages 5 to 25.

Contrast with cohort. All cohort studies are longitudinal. But not all longitudinal studies follow a specifically defined cohort - the term is broader. On the MCAT, “longitudinal” emphasizes repeated measurement over time; “cohort” emphasizes a group followed together.

Case-Control Study

Definition. An observational design that starts with outcome, then looks backward for exposure. Two groups are identified: people who have the disease (cases) and people who don’t (controls, otherwise similar). Their histories are compared to identify exposures that differ.

Example. Researchers find 100 people with pancreatic cancer and 100 matched controls without it. They ask both groups about decades of coffee consumption, to see if coffee drinkers are overrepresented among the cases.

Contrast with prospective cohort. Prospective cohort: start with exposure, wait for outcome. Case-control: start with outcome, look back at exposure. Case-control is faster and cheaper for rare diseases but more vulnerable to recall bias.

Clinical Trial / Randomized Controlled Trial (RCT)

Definition. An interventional study where the researcher assigns participants to a treatment or a control group. In a randomized controlled trial, assignment is by chance.

Example. 1,000 patients with depression are randomly assigned to either a new drug or a placebo. After 12 weeks, symptom scores are compared.

RCTs are the gold standard for causal inference because randomization balances known and unknown confounders between groups. Still, they are not always feasible or ethical (you cannot randomly assign smoking).

Experimental Study

Definition. A study in which the researcher manipulates an independent variable to see its effect on a dependent variable, with random assignment.

An RCT is one kind of experimental study. Lab-based experiments (e.g., a psychologist manipulating the gender of a name on a résumé) are another.

Quasi-Experimental Design

Definition. An experimental-style study that lacks random assignment. The researcher still manipulates an independent variable (or a naturally occurring one), but participants are not randomly assigned to conditions.

Example. A school district adopts a new math curriculum in three schools and compares outcomes to three neighboring schools that kept the old curriculum. Since the researcher didn’t randomize, the schools may differ in ways that confound the result.

Contrast with true experiment. True experiments randomize. Quasi-experiments don’t, which weakens causal claims.

Factorial Design

Definition. An experimental design that manipulates two or more independent variables simultaneously, with every combination represented. Notation like “3 × 2” means three levels of the first variable crossed with two levels of the second, producing six treatment conditions.

Example. Testing a drug at low, medium, and high doses (3 levels) with either morning or evening administration (2 levels). Total = 6 conditions.

Factorial designs allow researchers to check for interactions - does the effect of one variable depend on the level of another?

Observational Study

Definition. A study where the researcher observes without manipulating any variable. Participants are not assigned to conditions.

Cross-sectional, cohort, and case-control studies are all observational. Experiments are not.

Embedded Field Study

Definition. A qualitative research approach where observers pose as participants or embed themselves in a real-world setting.

Example. A sociologist works undercover as a waitress for six months to study the tipping norms of restaurant customers.

Retrospective vs. Prospective Chart Review

  • Retrospective chart study. Examines medical records that already exist, looking backward at events already recorded.
  • Prospective chart study. Sets up in advance what will be recorded going forward, and examines the charts as they accumulate.
Distinguish a prospective cohort study from a case-control study.
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Prospective cohort starts with an exposure (e.g., smoking status) and follows people forward to see who develops disease. Case-control starts with the outcome (cases have disease, controls don't) and looks backward at exposures. Cohort = exposure-first, forward in time. Case-control = outcome-first, backward in time.
What does a "3 × 2 factorial design" mean?
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A factorial design with two independent variables: the first has 3 levels, the second has 2 levels. All combinations are tested, producing 3 × 2 = 6 conditions. Allows the researcher to test main effects and interactions between the two variables.
Why is an RCT the gold standard for causal inference?
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Random assignment balances both known and unknown confounders across treatment and control groups on average. Any remaining post-treatment difference is attributable to the intervention rather than pre-existing group differences. Quasi-experiments lack this property.