What is a Controlled Experiment?
A controlled experiment assesses causal relationships between treatments and outcomes by systematically manipulating the treatments and controlling other variables. The goal is to determine whether the treatment causes changes in the outcomes.
In a controlled experiment, the independent variable is the treatment that researchers control. They set both the form of treatment (e.g., dosage) and which participants receive it. The outcome variable is the dependent variable, which the researchers measure.
Extraneous variables can also affect the outcome even though they aren’t treatments. They are problematic because they provide alternative explanations for changes in the outcomes. These confounders might cause the changes rather than the treatment. Consequently, controlled experiments find ways to control these extraneous variables.
Hence, two critical components of controlled experiments are controlling the treatment and the extraneous variables. Both are crucial for establishing causal relationships.
Additionally, these studies rigorously follow a standardized procedure, making it easy for other studies to replicate.
Learn more about Independent and Dependent Variables: Differences & Examples.
How to Control Variables in Experiments
Controlled experiments try to minimize systematic differences between treated and untreated participants other than the treatment itself. This control isolates the effects of the treatment. There are many ways to control variables in an experiment. The following are some of them.
Standardized Methods in Controlled Experiments
Using the same equipment, procedures, and environments reduces the chances of other factors affecting the outcome. Standardization controls extraneous variables by lowering their overall variability such that everything is the same for all participants.
For example, researchers conducted an experiment assessing the effects of caffeine on reaction time. They controlled conditions by using a quiet lab with regulated lighting. All participants used identical laptops to complete reaction time tests. Researchers administered caffeine in pre-measured capsules and required participants to abstain from caffeine for 12 hours before testing. By controlling these factors, the team reduced noise from variables like distractions, device differences, or varying caffeine levels in the participants’ systems. This consistency allowed the researchers to attribute changes in reaction time more confidently to the caffeine dose.
Use a Control Group
Most controlled experiments include a treatment and control group. The treatment group receives the treatment, while the control group does not. Ideally, the experimental manipulation is the only difference between the groups. Researchers estimate the treatment effect by comparing the group outcomes.
For example, researchers test whether a fertilizer improves crop yield in a controlled experiment. They divided a field into two sections: one received the fertilizer (treatment group), and the other did not (control group). Both sections had the same soil type, irrigation, planting schedule, and climatic conditions. At harvest, the researchers found the treatment group produced 20% more wheat than the control. By comparing the two groups, they estimated the fertilizer’s effect while maintaining environmental consistency.
Learn more about Control Groups in Experiments.
Random Assignment
Random assignment helps equalize the treatment and control groups in a controlled experiment. The randomness helps ensure that one group doesn’t have properties that are systematically different from the other group. This method controls extraneous variables by equalizing them between groups.
For example, a controlled experiment examined whether a new teaching method improves test scores. Researchers randomly assigned students to either the new or traditional method groups. This random assignment ensured that factors like prior knowledge, motivation, and ability were equally distributed. Consequently, researchers can more confidently attribute differences in test scores to the teaching method rather than extraneous variables.
Learn more about Random Assignment.
Blinding in a Controlled Experiment
Knowledge of group assignments is an extraneous variable that can lead researchers to unconsciously influence measurements and participants to alter their behavior based on expectations.
Blinding helps control these extraneous variables by hiding group assignments from researchers and participants to prevent that knowledge from influencing the results. In a double-blinded controlled experiment, participants and researchers don’t know who gets the intervention to guard against sneaky biases that might creep into the results.
Statistical Control
In an experiment, it’s challenging to control all extraneous variables. Individuals and experiences vary greatly, and some of these characteristics can affect the outcome. Fortunately, if researchers can measure them, they can use statistical analyses, such as regression, to control them.
Drawbacks of Controlled Experiments
Controlled experiments are great for finding causal relationships but have some drawbacks.
All that careful planning, control, and lab time tends to make them more expensive. Additionally, while controlled experiments have high internal validity thanks to the meticulously managed research environment and procedures, that artificial environment also reduces the generalizability of the results to the real world—it lowers external validity.
Finally, in some settings, it’s impossible or unethical to control the independent variable, making a controlled experiment impossible. In those cases, you might need to use a quasi-experiment or observational study.
In some experiments, it’s more efficient to manipulate multiple factors simultaneously. To learn more, read Factorial Designs Explained: Testing Multiple Factors.
Learn more about Internal and External Validity and Randomized Controlled Trials (RCTs).
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