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- Controlled Experiments | Methods & Examples of Control
Controlled Experiments | Methods & Examples of Control
Published on 19 April 2022 by Pritha Bhandari . Revised on 10 October 2022.
In experiments , researchers manipulate independent variables to test their effects on dependent variables. In a controlled experiment , all variables other than the independent variable are controlled or held constant so they don’t influence the dependent variable.
Controlling variables can involve:
- Holding variables at a constant or restricted level (e.g., keeping room temperature fixed)
- Measuring variables to statistically control for them in your analyses
- Balancing variables across your experiment through randomisation (e.g., using a random order of tasks)
Table of contents
Why does control matter in experiments, methods of control, problems with controlled experiments, frequently asked questions about controlled experiments.
Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables.
- Your independent variable is the colour used in advertising.
- Your dependent variable is the price that participants are willing to pay for a standard fast food meal.
Extraneous variables are factors that you’re not interested in studying, but that can still influence the dependent variable. For strong internal validity, you need to remove their effects from your experiment.
- Design and description of the meal
- Study environment (e.g., temperature or lighting)
- Participant’s frequency of buying fast food
- Participant’s familiarity with the specific fast food brand
- Participant’s socioeconomic status
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You can control some variables by standardising your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., advert colour) should be systematically changed between groups.
Other extraneous variables can be controlled through your sampling procedures . Ideally, you’ll select a sample that’s representative of your target population by using relevant inclusion and exclusion criteria (e.g., including participants from a specific income bracket, and not including participants with colour blindness).
By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.
After gathering your participants, you’ll need to place them into groups to test different independent variable treatments. The types of groups and method of assigning participants to groups will help you implement control in your experiment.
Control groups
Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment, and compare the outcome with your experimental treatment.
You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.
- A control group that’s presented with red advertisements for a fast food meal
- An experimental group that’s presented with green advertisements for the same fast food meal
Random assignment
To avoid systematic differences between the participants in your control and treatment groups, you should use random assignment .
This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .
Random assignment is a hallmark of a ‘true experiment’ – it differentiates true experiments from quasi-experiments .
Masking (blinding)
Masking in experiments means hiding condition assignment from participants or researchers – or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs.
Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses. In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses.
Using masking means that participants don’t know whether they’re in the control group or the experimental group. This helps you control biases from participants or researchers that could influence your study results.
Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.
Difficult to control all variables
Especially in research with human participants, it’s impossible to hold all extraneous variables constant, because every individual has different experiences that may influence their perception, attitudes, or behaviors.
But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.
Risk of low external validity
Controlled experiments have disadvantages when it comes to external validity – the extent to which your results can be generalised to broad populations and settings.
The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.
There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritise control or generalisability in your experiment.
Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.
To design a successful experiment, first identify:
- A testable hypothesis
- One or more independent variables that you will manipulate
- One or more dependent variables that you will measure
When designing the experiment, first decide:
- How your variable(s) will be manipulated
- How you will control for any potential confounding or lurking variables
- How many subjects you will include
- How you will assign treatments to your subjects
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Pritha Bhandari
Experimental Method In Psychology
Saul McLeod, PhD
Editor-in-Chief for Simply Psychology
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
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Olivia Guy-Evans, MSc
Associate Editor for Simply Psychology
BSc (Hons) Psychology, MSc Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
On This Page:
The experimental method involves the manipulation of variables to establish cause-and-effect relationships. The key features are controlled methods and the random allocation of participants into controlled and experimental groups .
What is an Experiment?
An experiment is an investigation in which a hypothesis is scientifically tested. An independent variable (the cause) is manipulated in an experiment, and the dependent variable (the effect) is measured; any extraneous variables are controlled.
An advantage is that experiments should be objective. The researcher’s views and opinions should not affect a study’s results. This is good as it makes the data more valid and less biased.
There are three types of experiments you need to know:
1. Lab Experiment
A laboratory experiment in psychology is a research method in which the experimenter manipulates one or more independent variables and measures the effects on the dependent variable under controlled conditions.
A laboratory experiment is conducted under highly controlled conditions (not necessarily a laboratory) where accurate measurements are possible.
The researcher uses a standardized procedure to determine where the experiment will take place, at what time, with which participants, and in what circumstances.
Participants are randomly allocated to each independent variable group.
Examples are Milgram’s experiment on obedience and Loftus and Palmer’s car crash study .
- Strength : It is easier to replicate (i.e., copy) a laboratory experiment. This is because a standardized procedure is used.
- Strength : They allow for precise control of extraneous and independent variables. This allows a cause-and-effect relationship to be established.
- Limitation : The artificiality of the setting may produce unnatural behavior that does not reflect real life, i.e., low ecological validity. This means it would not be possible to generalize the findings to a real-life setting.
- Limitation : Demand characteristics or experimenter effects may bias the results and become confounding variables .
2. Field Experiment
A field experiment is a research method in psychology that takes place in a natural, real-world setting. It is similar to a laboratory experiment in that the experimenter manipulates one or more independent variables and measures the effects on the dependent variable.
However, in a field experiment, the participants are unaware they are being studied, and the experimenter has less control over the extraneous variables .
Field experiments are often used to study social phenomena, such as altruism, obedience, and persuasion. They are also used to test the effectiveness of interventions in real-world settings, such as educational programs and public health campaigns.
An example is Holfing’s hospital study on obedience .
- Strength : behavior in a field experiment is more likely to reflect real life because of its natural setting, i.e., higher ecological validity than a lab experiment.
- Strength : Demand characteristics are less likely to affect the results, as participants may not know they are being studied. This occurs when the study is covert.
- Limitation : There is less control over extraneous variables that might bias the results. This makes it difficult for another researcher to replicate the study in exactly the same way.
3. Natural Experiment
A natural experiment in psychology is a research method in which the experimenter observes the effects of a naturally occurring event or situation on the dependent variable without manipulating any variables.
Natural experiments are conducted in the day (i.e., real life) environment of the participants, but here, the experimenter has no control over the independent variable as it occurs naturally in real life.
Natural experiments are often used to study psychological phenomena that would be difficult or unethical to study in a laboratory setting, such as the effects of natural disasters, policy changes, or social movements.
For example, Hodges and Tizard’s attachment research (1989) compared the long-term development of children who have been adopted, fostered, or returned to their mothers with a control group of children who had spent all their lives in their biological families.
Here is a fictional example of a natural experiment in psychology:
Researchers might compare academic achievement rates among students born before and after a major policy change that increased funding for education.
In this case, the independent variable is the timing of the policy change, and the dependent variable is academic achievement. The researchers would not be able to manipulate the independent variable, but they could observe its effects on the dependent variable.
- Strength : behavior in a natural experiment is more likely to reflect real life because of its natural setting, i.e., very high ecological validity.
- Strength : Demand characteristics are less likely to affect the results, as participants may not know they are being studied.
- Strength : It can be used in situations in which it would be ethically unacceptable to manipulate the independent variable, e.g., researching stress .
- Limitation : They may be more expensive and time-consuming than lab experiments.
- Limitation : There is no control over extraneous variables that might bias the results. This makes it difficult for another researcher to replicate the study in exactly the same way.
Key Terminology
Ecological validity.
The degree to which an investigation represents real-life experiences.
Experimenter effects
These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.
Demand characteristics
The clues in an experiment lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).
Independent variable (IV)
The variable the experimenter manipulates (i.e., changes) is assumed to have a direct effect on the dependent variable.
Dependent variable (DV)
Variable the experimenter measures. This is the outcome (i.e., the result) of a study.
Extraneous variables (EV)
All variables which are not independent variables but could affect the results (DV) of the experiment. EVs should be controlled where possible.
Confounding variables
Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.
Random Allocation
Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of participating in each condition.
The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.
Order effects
Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:
(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;
(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.
