lab experiment psychology pros and cons

Experimental Method In Psychology

Saul McLeod, PhD

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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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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.

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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.

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• Lab Experiment

What do you think of when you hear the word "laboratory"? Do you picture people in white coats and goggles and gloves standing over a table with beakers and tubes? Well, that picture is pretty close to reality in some cases. In others, laboratory experiments, especially in psychology, focus more on observing behaviours in highly controlled settings to establish causal conclusions. Let's explore lab experiments further. 

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The aim of lab experiments is to identify if observed changes in the      are caused by the        .

Is it difficult to generalise results from lab experiments to real-life settings? 

Demand characteristics lower the           of the research.

True or false: there is more likelihood of demand characteristics influencing lab experiments than field experiments.

A researcher wanted to explore how driving conditions affected speeding. Which type of experimental method is the researcher more likely to use? 

A researcher wanted to explore if sleep deprivation affected cognitive abilities. Which type of experimental method is the researcher more likely to use? 

Are lab experiments easy to replicate? 

True or false: Participants are aware that they are taking part in the lab experiment and sometimes may not know the aim of the investigation.

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• We are going to delve into the topic of lab experiments in the context of psychology.
• We will start by looking at the lab experiment definition and how lab experiments are used in psychology.
• Moving on from this, we will look at how lab experiment examples in psychology and cognitive lab experiments may be conducted.
• And to finish off, we will also explore the strengths and weaknesses of lab experiments.

Lab Experiment Psychology Definition

You can probably guess from the name that lab experiments occur in lab settings. Although this is not always the case, they can sometimes occur in other controlled environments. The purpose of lab experiments is to identify the cause and effect of a phenomenon through experimentation.

A lab experiment is an experiment that uses a carefully controlled setting and standardised procedure to accurately measure how changes in the independent variable (IV; variable that changes) affects the dependent variable (DV; variable measured).

In lab experiments, the IV is what the researcher predicts as the cause of a phenomenon, and the dependent variable is what the researcher predicts as the effect of a phenomenon.

Lab Experiment: P sychology

Lab experiments in psychology are used when trying to establish causal relationships between variables . For example, a researcher would use a lab experiment if they were investigating how sleep affects memory recall.

The majority of psychologists think of psychology as a form of science. Therefore, they argue that the protocol used in psychological research should resemble those used in the natural sciences. For research to be established as scientific , three essential features should be considered:

• Empiricism - the findings should be observable via the five senses.
• Reliability - if the study was replicated, similar results should be found.
• Validity - the investigation should accurately measure what it intends to.

But do lab experiments fulfil these requirements of natural sciences research? If done correctly, then yes. Lab experiments are empirical as they involve the researcher observing changes occurring in the DV. Reliability is established by using a standardised procedure in lab experiments .

A standardised procedure is a protocol that states how the experiment will be carried out. This allows the researcher to ensure the same protocol is used for each participant, increasing the study's internal reliability.

Standardised procedures are also used to help other researchers replicate the study to identify if they measure similar results.

Dissimilar results reflect low reliability.

Validity is another feature of a lab experiment considered. Lab experiments are conducted in a carefully controlled setting where the researcher has the most control compared to other experiments to prevent extraneous variables from affecting the DV .

Extraneous variables are factors other than the IV that affect the DV; as these are variables that the researcher is not interested in investigating, these reduce the validity of the research.

There are issues of validity in lab experiments, which we'll get into a bit later!

Lab Experiment Examples: Asch's Conformity Study

The Asch (1951) conformity study is an example of a lab experiment. The investigation aimed to identify if the presence and influence of others would pressure participants to change their response to a straightforward question. Participants were given two pieces of paper, one depicting a 'target line' and another three, one of which resembled the 'target line' and the others of different lengths.

The participants were put in groups of eight. Unknown to the participants, the other seven were confederates (participants who were secretly part of the research team) who were instructed to give the wrong answer. If the actual participant changed their answer in response, this would be an example of conformity .

Asch controlled the location where the investigation took place, constructed a contrived scenario and even controlled the confederates who would affect the behaviour of the actual participants to measure the DV.

Some other famous examples of research that are lab experiment examples include research conducted by Milgram (the obedience study) and Loftus and Palmer's eyewitness testimony accuracy study . These researchers likely used this method because of some of their strengths , e.g., their high level of control .

Lab Experiment Examples: Cognitive Lab Experiments

Let's look at what a cognitive lab experiment may entail. Suppose a researcher is interested in investigating how sleep affects memory scores using the MMSE test. In the theoretical study , an equal number of participants were randomly allocated into two groups; sleep-deprived versus well-rested. Both groups completed the memory test after a whole night of sleep or staying awake all night.

In this research scenario , the DV can be identified as memory test scores and the IV as whether participants were sleep-deprived or well-rested.

Some examples of extraneous variables the study controlled include researchers ensuring participants did not fall asleep, the participants took the test at the same time, and participants in the well-rested group slept for the same time.

Lab Experiment Advantages and Disadvantages

It's important to consider the advantages and disadvantages of laboratory experiments . Advantages include the highly controlled setting of lab experiments, the standardised procedures and causal conclusions that can be drawn. Disadvantages include the low ecological validity of lab experiments and demand characteristics participants may present.

Strengths of Lab Experiments: Highly Controlled

Laboratory experiments are conducted in a well-controlled setting. All the variables, including extraneous and confounding variables , are rigidly controlled in the investigation. Therefore, the risk of experimental findings being affected by extraneous or confounding variables is reduced . As a result, the well-controlled design of laboratory experiments implies the research has high internal validity .

Internal validity means the study uses measures and protocols that measure exactly what it intends to, i.e. how only the changes in the IV affect the DV.

Strengths of Lab Experiments: Standardised Procedures

Laboratory experiments have standardised procedures, which means the experiments are replicable , and all participants are tested under the same conditions. T herefore, standardised procedures allow others to replicate the study to identify whether the research is reliable and that the findings are not a one-off result. As a result, the replicability of laboratory experiments allows researchers to verify the study's reliability .

Strengths of Lab Experiments: Causal Conclusions

A well-designed laboratory experiment can draw causal conclusions. Ideally, a laboratory experiment can rigidly control all the variables , including extraneous and confounding variables. Therefore, laboratory experiments provide great confidence to researchers that the IV causes any observed changes in DV.

Weaknesses of Lab Experiments

In the following, we will present the disadvantages of laboratory experiments. This discusses ecological validity and demand characteristics.

Weaknesses of Lab Experiments: Low Ecological Validity

Laboratory experiments have low ecological validity because they are conducted in an artificial study that does not reflect a real-life setting . As a result, findings generated in laboratory experiments can be difficult to generalise to real life due to the low mundane realism. Mundane realism reflects the extent to which lab experiment materials are similar to real-life events.

Weaknesses of Lab Experiments: Demand Characteristics

A disadvantage of laboratory experiments is that the research setting may lead to demand characteristics .

Demand characteristics are the cues that make participants aware of what the experimenter expects to find or how participants are expected to behave.

The participants are aware they are involved in an experiment. So, participants may have some ideas of what is expected of them in the investigation, which may influence their behaviours. As a result, the demand characteristics presented in laboratory experiments can arguably change the research outcome , reducing the findings' validity .

Lab Experiment - Key takeaways

The lab experiment definition is an experiment that uses a carefully controlled setting and standardised procedure to establish how changes in the independent variable (IV; variable that changes) affect the dependent variable (DV; variable measured).

Psychologists aim to ensure that lab experiments are scientific and must be empirical, reliable and valid.

The Asch (1951) conformity study is an example of a lab experiment. The investigation aimed to identify if the presence and influence of others would pressure participants to change their response to a straightforward question.

The advantages of lab experiments are high internal validity, standardised procedures and the ability to draw causal conclusions.

The disadvantages of lab experiments are low ecological validity and demand characteristics.

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Frequently Asked Questions about Lab Experiment

What is a lab experiment?

A lab experiment is an experiment that uses a carefully controlled setting and standardised procedure to establish how changes in the independent variable (IV; variable that changes) affects the dependent variable (DV; variable measured).

What is the purpose of lab experiments?

Lab experiments investigate cause-and-effect. They aim to determine the effect of changes in the independent variable on the dependent variable. 

What is a lab experiment and field experiment?

A field experiment is an experiment conducted in a natural, everyday setting. The experimenter still controls the IV; however, extraneous and confounding variables may be difficult to control due to the natural setting.

Similar, to filed experiments researchers, can control the IV and extraneous variables. However, this takes place in an artificial setting such as a lab. 

Why would a psychologist use a laboratory experiment? 

A psychologist may use a lab experiment when trying to establish the causal relationships between variables to explain a phenomenon. 

Why is lab experience important?

Lab experience allows researchers to scientifically determine whether a hypothesis/ theory should be accepted or rejected. 

What is a lab experiment example? 

The research conducted by Loftus and Palmer (accuracy of eyewitness testimony) and Milgram (obedience) used a lab experiment design. These experimental designs give the researcher high control, allowing them to control extraneous and independent variables.

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16 Advantages and Disadvantages of Experimental Research

How do you make sure that a new product, theory, or idea has validity? There are multiple ways to test them, with one of the most common being the use of experimental research. When there is complete control over one variable, the other variables can be manipulated to determine the value or validity that has been proposed.

Then, through a process of monitoring and administration, the true effects of what is being studied can be determined. This creates an accurate outcome so conclusions about the final value potential. It is an efficient process, but one that can also be easily manipulated to meet specific metrics if oversight is not properly performed.

Here are the advantages and disadvantages of experimental research to consider.

What Are the Advantages of Experimental Research?

1. It provides researchers with a high level of control. By being able to isolate specific variables, it becomes possible to determine if a potential outcome is viable. Each variable can be controlled on its own or in different combinations to study what possible outcomes are available for a product, theory, or idea as well. This provides a tremendous advantage in an ability to find accurate results.

2. There is no limit to the subject matter or industry involved. Experimental research is not limited to a specific industry or type of idea. It can be used in a wide variety of situations. Teachers might use experimental research to determine if a new method of teaching or a new curriculum is better than an older system. Pharmaceutical companies use experimental research to determine the viability of a new product.

3. Experimental research provides conclusions that are specific. Because experimental research provides such a high level of control, it can produce results that are specific and relevant with consistency. It is possible to determine success or failure, making it possible to understand the validity of a product, theory, or idea in a much shorter amount of time compared to other verification methods. You know the outcome of the research because you bring the variable to its conclusion.

4. The results of experimental research can be duplicated. Experimental research is straightforward, basic form of research that allows for its duplication when the same variables are controlled by others. This helps to promote the validity of a concept for products, ideas, and theories. This allows anyone to be able to check and verify published results, which often allows for better results to be achieved, because the exact steps can produce the exact results.

5. Natural settings can be replicated with faster speeds. When conducting research within a laboratory environment, it becomes possible to replicate conditions that could take a long time so that the variables can be tested appropriately. This allows researchers to have a greater control of the extraneous variables which may exist as well, limiting the unpredictability of nature as each variable is being carefully studied.

6. Experimental research allows cause and effect to be determined. The manipulation of variables allows for researchers to be able to look at various cause-and-effect relationships that a product, theory, or idea can produce. It is a process which allows researchers to dig deeper into what is possible, showing how the various variable relationships can provide specific benefits. In return, a greater understanding of the specifics within the research can be understood, even if an understanding of why that relationship is present isn’t presented to the researcher.

7. It can be combined with other research methods. This allows experimental research to be able to provide the scientific rigor that may be needed for the results to stand on their own. It provides the possibility of determining what may be best for a specific demographic or population while also offering a better transference than anecdotal research can typically provide.

What Are the Disadvantages of Experimental Research?

1. Results are highly subjective due to the possibility of human error. Because experimental research requires specific levels of variable control, it is at a high risk of experiencing human error at some point during the research. Any error, whether it is systemic or random, can reveal information about the other variables and that would eliminate the validity of the experiment and research being conducted.

2. Experimental research can create situations that are not realistic. The variables of a product, theory, or idea are under such tight controls that the data being produced can be corrupted or inaccurate, but still seem like it is authentic. This can work in two negative ways for the researcher. First, the variables can be controlled in such a way that it skews the data toward a favorable or desired result. Secondly, the data can be corrupted to seem like it is positive, but because the real-life environment is so different from the controlled environment, the positive results could never be achieved outside of the experimental research.

3. It is a time-consuming process. For it to be done properly, experimental research must isolate each variable and conduct testing on it. Then combinations of variables must also be considered. This process can be lengthy and require a large amount of financial and personnel resources. Those costs may never be offset by consumer sales if the product or idea never makes it to market. If what is being tested is a theory, it can lead to a false sense of validity that may change how others approach their own research.

4. There may be ethical or practical problems with variable control. It might seem like a good idea to test new pharmaceuticals on animals before humans to see if they will work, but what happens if the animal dies because of the experimental research? Or what about human trials that fail and cause injury or death? Experimental research might be effective, but sometimes the approach has ethical or practical complications that cannot be ignored. Sometimes there are variables that cannot be manipulated as it should be so that results can be obtained.

5. Experimental research does not provide an actual explanation. Experimental research is an opportunity to answer a Yes or No question. It will either show you that it will work or it will not work as intended. One could argue that partial results could be achieved, but that would still fit into the “No” category because the desired results were not fully achieved. The answer is nice to have, but there is no explanation as to how you got to that answer. Experimental research is unable to answer the question of “Why” when looking at outcomes.

6. Extraneous variables cannot always be controlled. Although laboratory settings can control extraneous variables, natural environments provide certain challenges. Some studies need to be completed in a natural setting to be accurate. It may not always be possible to control the extraneous variables because of the unpredictability of Mother Nature. Even if the variables are controlled, the outcome may ensure internal validity, but do so at the expense of external validity. Either way, applying the results to the general population can be quite challenging in either scenario.

7. Participants can be influenced by their current situation. Human error isn’t just confined to the researchers. Participants in an experimental research study can also be influenced by extraneous variables. There could be something in the environment, such an allergy, that creates a distraction. In a conversation with a researcher, there may be a physical attraction that changes the responses of the participant. Even internal triggers, such as a fear of enclosed spaces, could influence the results that are obtained. It is also very common for participants to “go along” with what they think a researcher wants to see instead of providing an honest response.

8. Manipulating variables isn’t necessarily an objective standpoint. For research to be effective, it must be objective. Being able to manipulate variables reduces that objectivity. Although there are benefits to observing the consequences of such manipulation, those benefits may not provide realistic results that can be used in the future. Taking a sample is reflective of that sample and the results may not translate over to the general population.

9. Human responses in experimental research can be difficult to measure. There are many pressures that can be placed on people, from political to personal, and everything in-between. Different life experiences can cause people to react to the same situation in different ways. Not only does this mean that groups may not be comparable in experimental research, but it also makes it difficult to measure the human responses that are obtained or observed.

The advantages and disadvantages of experimental research show that it is a useful system to use, but it must be tightly controlled in order to be beneficial. It produces results that can be replicated, but it can also be easily influenced by internal or external influences that may alter the outcomes being achieved. By taking these key points into account, it will become possible to see if this research process is appropriate for your next product, theory, or idea.

7 Advantages and Disadvantages of Experimental Research

There are multiple ways to test and do research on new ideas, products, or theories. One of these ways is by experimental research. This is when the researcher has complete control over one set of the variable, and manipulates the others. A good example of this is pharmaceutical research. They will administer the new drug to one group of subjects, and not to the other, while monitoring them both. This way, they can tell the true effects of the drug by comparing them to people who are not taking it. With this type of research design, only one variable can be tested, which may make it more time consuming and open to error. However, if done properly, it is known as one of the most efficient and accurate ways to reach a conclusion. There are other things that go into the decision of whether or not to use experimental research, some bad and some good, let’s take a look at both of these.

The Advantages of Experimental Research

1. A High Level Of Control With experimental research groups, the people conducting the research have a very high level of control over their variables. By isolating and determining what they are looking for, they have a great advantage in finding accurate results.

2. Can Span Across Nearly All Fields Of Research Another great benefit of this type of research design is that it can be used in many different types of situations. Just like pharmaceutical companies can utilize it, so can teachers who want to test a new method of teaching. It is a basic, but efficient type of research.

3. Clear Cut Conclusions Since there is such a high level of control, and only one specific variable is being tested at a time, the results are much more relevant than some other forms of research. You can clearly see the success, failure, of effects when analyzing the data collected.

4. Many Variations Can Be Utilized There is a very wide variety of this type of research. Each can provide different benefits, depending on what is being explored. The investigator has the ability to tailor make the experiment for their own unique situation, while still remaining in the validity of the experimental research design.

The Disadvantages of Experimental Research

1. Largely Subject To Human Errors Just like anything, errors can occur. This is especially true when it comes to research and experiments. Any form of error, whether a systematic (error with the experiment) or random error (uncontrolled or unpredictable), or human errors such as revealing who the control group is, they can all completely destroy the validity of the experiment.

2. Can Create Artificial Situations By having such deep control over the variables being tested, it is very possible that the data can be skewed or corrupted to fit whatever outcome the researcher needs. This is especially true if it is being done for a business or market study.

3. Can Take An Extensive Amount of Time To Do Full Research With experimental testing individual experiments have to be done in order to fully research each variable. This can cause the testing to take a very long amount of time and use a large amount of resources and finances. These costs could transfer onto the company, which could inflate costs for consumers.

Important Facts About Experimental Research

• Experimental Research is most used in medical ways, with animals.
• Every single new medicine or drug is testing using this research design.
• There are countless variations of experimental research, including: probability, sequential, snowball, and quota.

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How the Experimental Method Works in Psychology

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The Experimental Process

Types of experiments, potential pitfalls of the experimental method.

The experimental method is a type of research procedure that involves manipulating variables to determine if there is a cause-and-effect relationship. The results obtained through the experimental method are useful but do not prove with 100% certainty that a singular cause always creates a specific effect. Instead, they show the probability that a cause will or will not lead to a particular effect.

At a Glance

While there are many different research techniques available, the experimental method allows researchers to look at cause-and-effect relationships. Using the experimental method, researchers randomly assign participants to a control or experimental group and manipulate levels of an independent variable. If changes in the independent variable lead to changes in the dependent variable, it indicates there is likely a causal relationship between them.

What Is the Experimental Method in Psychology?

The experimental method involves manipulating one variable to determine if this causes changes in another variable. This method relies on controlled research methods and random assignment of study subjects to test a hypothesis.

For example, researchers may want to learn how different visual patterns may impact our perception. Or they might wonder whether certain actions can improve memory . Experiments are conducted on many behavioral topics, including:

The scientific method forms the basis of the experimental method. This is a process used to determine the relationship between two variables—in this case, to explain human behavior .

Positivism is also important in the experimental method. It refers to factual knowledge that is obtained through observation, which is considered to be trustworthy.

When using the experimental method, researchers first identify and define key variables. Then they formulate a hypothesis, manipulate the variables, and collect data on the results. Unrelated or irrelevant variables are carefully controlled to minimize the potential impact on the experiment outcome.

History of the Experimental Method

The idea of using experiments to better understand human psychology began toward the end of the nineteenth century. Wilhelm Wundt established the first formal laboratory in 1879.

Wundt is often called the father of experimental psychology. He believed that experiments could help explain how psychology works, and used this approach to study consciousness .

Wundt coined the term "physiological psychology." This is a hybrid of physiology and psychology, or how the body affects the brain.

Other early contributors to the development and evolution of experimental psychology as we know it today include:

• Gustav Fechner (1801-1887), who helped develop procedures for measuring sensations according to the size of the stimulus
• Hermann von Helmholtz (1821-1894), who analyzed philosophical assumptions through research in an attempt to arrive at scientific conclusions
• Franz Brentano (1838-1917), who called for a combination of first-person and third-person research methods when studying psychology
• Georg Elias Müller (1850-1934), who performed an early experiment on attitude which involved the sensory discrimination of weights and revealed how anticipation can affect this discrimination

Key Terms to Know

To understand how the experimental method works, it is important to know some key terms.

Dependent Variable

The dependent variable is the effect that the experimenter is measuring. If a researcher was investigating how sleep influences test scores, for example, the test scores would be the dependent variable.

Independent Variable

The independent variable is the variable that the experimenter manipulates. In the previous example, the amount of sleep an individual gets would be the independent variable.

A hypothesis is a tentative statement or a guess about the possible relationship between two or more variables. In looking at how sleep influences test scores, the researcher might hypothesize that people who get more sleep will perform better on a math test the following day. The purpose of the experiment, then, is to either support or reject this hypothesis.

Operational definitions are necessary when performing an experiment. When we say that something is an independent or dependent variable, we must have a very clear and specific definition of the meaning and scope of that variable.

Extraneous Variables

Extraneous variables are other variables that may also affect the outcome of an experiment. Types of extraneous variables include participant variables, situational variables, demand characteristics, and experimenter effects. In some cases, researchers can take steps to control for extraneous variables.

Demand Characteristics

Demand characteristics are subtle hints that indicate what an experimenter is hoping to find in a psychology experiment. This can sometimes cause participants to alter their behavior, which can affect the results of the experiment.

Intervening Variables

Intervening variables are factors that can affect the relationship between two other variables. 

Confounding Variables

Confounding variables are variables that can affect the dependent variable, but that experimenters cannot control for. Confounding variables can make it difficult to determine if the effect was due to changes in the independent variable or if the confounding variable may have played a role.

Psychologists, like other scientists, use the scientific method when conducting an experiment. The scientific method is a set of procedures and principles that guide how scientists develop research questions, collect data, and come to conclusions.

The five basic steps of the experimental process are:

• Identifying a problem to study
• Devising the research protocol
• Conducting the experiment
• Analyzing the data collected
• Sharing the findings (usually in writing or via presentation)

Most psychology students are expected to use the experimental method at some point in their academic careers. Learning how to conduct an experiment is important to understanding how psychologists prove and disprove theories in this field.

There are a few different types of experiments that researchers might use when studying psychology. Each has pros and cons depending on the participants being studied, the hypothesis, and the resources available to conduct the research.

Lab Experiments

Lab experiments are common in psychology because they allow experimenters more control over the variables. These experiments can also be easier for other researchers to replicate. The drawback of this research type is that what takes place in a lab is not always what takes place in the real world.

Field Experiments

Sometimes researchers opt to conduct their experiments in the field. For example, a social psychologist interested in researching prosocial behavior might have a person pretend to faint and observe how long it takes onlookers to respond.

This type of experiment can be a great way to see behavioral responses in realistic settings. But it is more difficult for researchers to control the many variables existing in these settings that could potentially influence the experiment's results.

Quasi-Experiments

While lab experiments are known as true experiments, researchers can also utilize a quasi-experiment. Quasi-experiments are often referred to as natural experiments because the researchers do not have true control over the independent variable.

A researcher looking at personality differences and birth order, for example, is not able to manipulate the independent variable in the situation (personality traits). Participants also cannot be randomly assigned because they naturally fall into pre-existing groups based on their birth order.

So why would a researcher use a quasi-experiment? This is a good choice in situations where scientists are interested in studying phenomena in natural, real-world settings. It's also beneficial if there are limits on research funds or time.

Field experiments can be either quasi-experiments or true experiments.

Examples of the Experimental Method in Use

The experimental method can provide insight into human thoughts and behaviors, Researchers use experiments to study many aspects of psychology.

A 2019 study investigated whether splitting attention between electronic devices and classroom lectures had an effect on college students' learning abilities. It found that dividing attention between these two mediums did not affect lecture comprehension. However, it did impact long-term retention of the lecture information, which affected students' exam performance.

An experiment used participants' eye movements and electroencephalogram (EEG) data to better understand cognitive processing differences between experts and novices. It found that experts had higher power in their theta brain waves than novices, suggesting that they also had a higher cognitive load.

A study looked at whether chatting online with a computer via a chatbot changed the positive effects of emotional disclosure often received when talking with an actual human. It found that the effects were the same in both cases.

One experimental study evaluated whether exercise timing impacts information recall. It found that engaging in exercise prior to performing a memory task helped improve participants' short-term memory abilities.

Sometimes researchers use the experimental method to get a bigger-picture view of psychological behaviors and impacts. For example, one 2018 study examined several lab experiments to learn more about the impact of various environmental factors on building occupant perceptions.

A 2020 study set out to determine the role that sensation-seeking plays in political violence. This research found that sensation-seeking individuals have a higher propensity for engaging in political violence. It also found that providing access to a more peaceful, yet still exciting political group helps reduce this effect.

While the experimental method can be a valuable tool for learning more about psychology and its impacts, it also comes with a few pitfalls.

Experiments may produce artificial results, which are difficult to apply to real-world situations. Similarly, researcher bias can impact the data collected. Results may not be able to be reproduced, meaning the results have low reliability .

Since humans are unpredictable and their behavior can be subjective, it can be hard to measure responses in an experiment. In addition, political pressure may alter the results. The subjects may not be a good representation of the population, or groups used may not be comparable.

And finally, since researchers are human too, results may be degraded due to human error.

What This Means For You

Every psychological research method has its pros and cons. The experimental method can help establish cause and effect, and it's also beneficial when research funds are limited or time is of the essence.

At the same time, it's essential to be aware of this method's pitfalls, such as how biases can affect the results or the potential for low reliability. Keeping these in mind can help you review and assess research studies more accurately, giving you a better idea of whether the results can be trusted or have limitations.

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American Psychological Association. Experimental psychology studies human and animals .

Mayrhofer R, Kuhbandner C, Lindner C. The practice of experimental psychology: An inevitably postmodern endeavor . Front Psychol . 2021;11:612805. doi:10.3389/fpsyg.2020.612805

Mandler G. A History of Modern Experimental Psychology .

Stanford University. Wilhelm Maximilian Wundt . Stanford Encyclopedia of Philosophy.

Britannica. Gustav Fechner .

Britannica. Hermann von Helmholtz .

Meyer A, Hackert B, Weger U. Franz Brentano and the beginning of experimental psychology: implications for the study of psychological phenomena today . Psychol Res . 2018;82:245-254. doi:10.1007/s00426-016-0825-7

Britannica. Georg Elias Müller .

McCambridge J, de Bruin M, Witton J.  The effects of demand characteristics on research participant behaviours in non-laboratory settings: A systematic review .  PLoS ONE . 2012;7(6):e39116. doi:10.1371/journal.pone.0039116

Laboratory experiments . In: The Sage Encyclopedia of Communication Research Methods. Allen M, ed. SAGE Publications, Inc. doi:10.4135/9781483381411.n287

Schweizer M, Braun B, Milstone A. Research methods in healthcare epidemiology and antimicrobial stewardship — quasi-experimental designs . Infect Control Hosp Epidemiol . 2016;37(10):1135-1140. doi:10.1017/ice.2016.117

Glass A, Kang M. Dividing attention in the classroom reduces exam performance . Educ Psychol . 2019;39(3):395-408. doi:10.1080/01443410.2018.1489046

Keskin M, Ooms K, Dogru AO, De Maeyer P. Exploring the cognitive load of expert and novice map users using EEG and eye tracking . ISPRS Int J Geo-Inf . 2020;9(7):429. doi:10.3390.ijgi9070429

Ho A, Hancock J, Miner A. Psychological, relational, and emotional effects of self-disclosure after conversations with a chatbot . J Commun . 2018;68(4):712-733. doi:10.1093/joc/jqy026

Haynes IV J, Frith E, Sng E, Loprinzi P. Experimental effects of acute exercise on episodic memory function: Considerations for the timing of exercise . Psychol Rep . 2018;122(5):1744-1754. doi:10.1177/0033294118786688

Torresin S, Pernigotto G, Cappelletti F, Gasparella A. Combined effects of environmental factors on human perception and objective performance: A review of experimental laboratory works . Indoor Air . 2018;28(4):525-538. doi:10.1111/ina.12457

Schumpe BM, Belanger JJ, Moyano M, Nisa CF. The role of sensation seeking in political violence: An extension of the significance quest theory . J Personal Social Psychol . 2020;118(4):743-761. doi:10.1037/pspp0000223

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

6.2 Experimental Design

Learning objectives.

• Explain the difference between between-subjects and within-subjects experiments, list some of the pros and cons of each approach, and decide which approach to use to answer a particular research question.
• Define random assignment, distinguish it from random sampling, explain its purpose in experimental research, and use some simple strategies to implement it.
• Define what a control condition is, explain its purpose in research on treatment effectiveness, and describe some alternative types of control conditions.
• Define several types of carryover effect, give examples of each, and explain how counterbalancing helps to deal with them.

In this section, we look at some different ways to design an experiment. The primary distinction we will make is between approaches in which each participant experiences one level of the independent variable and approaches in which each participant experiences all levels of the independent variable. The former are called between-subjects experiments and the latter are called within-subjects experiments.

Between-Subjects Experiments

In a between-subjects experiment , each participant is tested in only one condition. For example, a researcher with a sample of 100 college students might assign half of them to write about a traumatic event and the other half write about a neutral event. Or a researcher with a sample of 60 people with severe agoraphobia (fear of open spaces) might assign 20 of them to receive each of three different treatments for that disorder. It is essential in a between-subjects experiment that the researcher assign participants to conditions so that the different groups are, on average, highly similar to each other. Those in a trauma condition and a neutral condition, for example, should include a similar proportion of men and women, and they should have similar average intelligence quotients (IQs), similar average levels of motivation, similar average numbers of health problems, and so on. This is a matter of controlling these extraneous participant variables across conditions so that they do not become confounding variables.

Random Assignment

The primary way that researchers accomplish this kind of control of extraneous variables across conditions is called random assignment , which means using a random process to decide which participants are tested in which conditions. Do not confuse random assignment with random sampling. Random sampling is a method for selecting a sample from a population, and it is rarely used in psychological research. Random assignment is a method for assigning participants in a sample to the different conditions, and it is an important element of all experimental research in psychology and other fields too.

In its strictest sense, random assignment should meet two criteria. One is that each participant has an equal chance of being assigned to each condition (e.g., a 50% chance of being assigned to each of two conditions). The second is that each participant is assigned to a condition independently of other participants. Thus one way to assign participants to two conditions would be to flip a coin for each one. If the coin lands heads, the participant is assigned to Condition A, and if it lands tails, the participant is assigned to Condition B. For three conditions, one could use a computer to generate a random integer from 1 to 3 for each participant. If the integer is 1, the participant is assigned to Condition A; if it is 2, the participant is assigned to Condition B; and if it is 3, the participant is assigned to Condition C. In practice, a full sequence of conditions—one for each participant expected to be in the experiment—is usually created ahead of time, and each new participant is assigned to the next condition in the sequence as he or she is tested. When the procedure is computerized, the computer program often handles the random assignment.

One problem with coin flipping and other strict procedures for random assignment is that they are likely to result in unequal sample sizes in the different conditions. Unequal sample sizes are generally not a serious problem, and you should never throw away data you have already collected to achieve equal sample sizes. However, for a fixed number of participants, it is statistically most efficient to divide them into equal-sized groups. It is standard practice, therefore, to use a kind of modified random assignment that keeps the number of participants in each group as similar as possible. One approach is block randomization . In block randomization, all the conditions occur once in the sequence before any of them is repeated. Then they all occur again before any of them is repeated again. Within each of these “blocks,” the conditions occur in a random order. Again, the sequence of conditions is usually generated before any participants are tested, and each new participant is assigned to the next condition in the sequence. Table 6.2 “Block Randomization Sequence for Assigning Nine Participants to Three Conditions” shows such a sequence for assigning nine participants to three conditions. The Research Randomizer website ( http://www.randomizer.org ) will generate block randomization sequences for any number of participants and conditions. Again, when the procedure is computerized, the computer program often handles the block randomization.

Table 6.2 Block Randomization Sequence for Assigning Nine Participants to Three Conditions

Random assignment is not guaranteed to control all extraneous variables across conditions. It is always possible that just by chance, the participants in one condition might turn out to be substantially older, less tired, more motivated, or less depressed on average than the participants in another condition. However, there are some reasons that this is not a major concern. One is that random assignment works better than one might expect, especially for large samples. Another is that the inferential statistics that researchers use to decide whether a difference between groups reflects a difference in the population takes the “fallibility” of random assignment into account. Yet another reason is that even if random assignment does result in a confounding variable and therefore produces misleading results, this is likely to be detected when the experiment is replicated. The upshot is that random assignment to conditions—although not infallible in terms of controlling extraneous variables—is always considered a strength of a research design.

Treatment and Control Conditions

Between-subjects experiments are often used to determine whether a treatment works. In psychological research, a treatment is any intervention meant to change people’s behavior for the better. This includes psychotherapies and medical treatments for psychological disorders but also interventions designed to improve learning, promote conservation, reduce prejudice, and so on. To determine whether a treatment works, participants are randomly assigned to either a treatment condition , in which they receive the treatment, or a control condition , in which they do not receive the treatment. If participants in the treatment condition end up better off than participants in the control condition—for example, they are less depressed, learn faster, conserve more, express less prejudice—then the researcher can conclude that the treatment works. In research on the effectiveness of psychotherapies and medical treatments, this type of experiment is often called a randomized clinical trial .

There are different types of control conditions. In a no-treatment control condition , participants receive no treatment whatsoever. One problem with this approach, however, is the existence of placebo effects. A placebo is a simulated treatment that lacks any active ingredient or element that should make it effective, and a placebo effect is a positive effect of such a treatment. Many folk remedies that seem to work—such as eating chicken soup for a cold or placing soap under the bedsheets to stop nighttime leg cramps—are probably nothing more than placebos. Although placebo effects are not well understood, they are probably driven primarily by people’s expectations that they will improve. Having the expectation to improve can result in reduced stress, anxiety, and depression, which can alter perceptions and even improve immune system functioning (Price, Finniss, & Benedetti, 2008).

Placebo effects are interesting in their own right (see Note 6.28 “The Powerful Placebo” ), but they also pose a serious problem for researchers who want to determine whether a treatment works. Figure 6.2 “Hypothetical Results From a Study Including Treatment, No-Treatment, and Placebo Conditions” shows some hypothetical results in which participants in a treatment condition improved more on average than participants in a no-treatment control condition. If these conditions (the two leftmost bars in Figure 6.2 “Hypothetical Results From a Study Including Treatment, No-Treatment, and Placebo Conditions” ) were the only conditions in this experiment, however, one could not conclude that the treatment worked. It could be instead that participants in the treatment group improved more because they expected to improve, while those in the no-treatment control condition did not.

Figure 6.2 Hypothetical Results From a Study Including Treatment, No-Treatment, and Placebo Conditions

Fortunately, there are several solutions to this problem. One is to include a placebo control condition , in which participants receive a placebo that looks much like the treatment but lacks the active ingredient or element thought to be responsible for the treatment’s effectiveness. When participants in a treatment condition take a pill, for example, then those in a placebo control condition would take an identical-looking pill that lacks the active ingredient in the treatment (a “sugar pill”). In research on psychotherapy effectiveness, the placebo might involve going to a psychotherapist and talking in an unstructured way about one’s problems. The idea is that if participants in both the treatment and the placebo control groups expect to improve, then any improvement in the treatment group over and above that in the placebo control group must have been caused by the treatment and not by participants’ expectations. This is what is shown by a comparison of the two outer bars in Figure 6.2 “Hypothetical Results From a Study Including Treatment, No-Treatment, and Placebo Conditions” .

Of course, the principle of informed consent requires that participants be told that they will be assigned to either a treatment or a placebo control condition—even though they cannot be told which until the experiment ends. In many cases the participants who had been in the control condition are then offered an opportunity to have the real treatment. An alternative approach is to use a waitlist control condition , in which participants are told that they will receive the treatment but must wait until the participants in the treatment condition have already received it. This allows researchers to compare participants who have received the treatment with participants who are not currently receiving it but who still expect to improve (eventually). A final solution to the problem of placebo effects is to leave out the control condition completely and compare any new treatment with the best available alternative treatment. For example, a new treatment for simple phobia could be compared with standard exposure therapy. Because participants in both conditions receive a treatment, their expectations about improvement should be similar. This approach also makes sense because once there is an effective treatment, the interesting question about a new treatment is not simply “Does it work?” but “Does it work better than what is already available?”

The Powerful Placebo

Many people are not surprised that placebos can have a positive effect on disorders that seem fundamentally psychological, including depression, anxiety, and insomnia. However, placebos can also have a positive effect on disorders that most people think of as fundamentally physiological. These include asthma, ulcers, and warts (Shapiro & Shapiro, 1999). There is even evidence that placebo surgery—also called “sham surgery”—can be as effective as actual surgery.

Medical researcher J. Bruce Moseley and his colleagues conducted a study on the effectiveness of two arthroscopic surgery procedures for osteoarthritis of the knee (Moseley et al., 2002). The control participants in this study were prepped for surgery, received a tranquilizer, and even received three small incisions in their knees. But they did not receive the actual arthroscopic surgical procedure. The surprising result was that all participants improved in terms of both knee pain and function, and the sham surgery group improved just as much as the treatment groups. According to the researchers, “This study provides strong evidence that arthroscopic lavage with or without débridement [the surgical procedures used] is not better than and appears to be equivalent to a placebo procedure in improving knee pain and self-reported function” (p. 85).

Research has shown that patients with osteoarthritis of the knee who receive a “sham surgery” experience reductions in pain and improvement in knee function similar to those of patients who receive a real surgery.

Army Medicine – Surgery – CC BY 2.0.

Within-Subjects Experiments

In a within-subjects experiment , each participant is tested under all conditions. Consider an experiment on the effect of a defendant’s physical attractiveness on judgments of his guilt. Again, in a between-subjects experiment, one group of participants would be shown an attractive defendant and asked to judge his guilt, and another group of participants would be shown an unattractive defendant and asked to judge his guilt. In a within-subjects experiment, however, the same group of participants would judge the guilt of both an attractive and an unattractive defendant.

The primary advantage of this approach is that it provides maximum control of extraneous participant variables. Participants in all conditions have the same mean IQ, same socioeconomic status, same number of siblings, and so on—because they are the very same people. Within-subjects experiments also make it possible to use statistical procedures that remove the effect of these extraneous participant variables on the dependent variable and therefore make the data less “noisy” and the effect of the independent variable easier to detect. We will look more closely at this idea later in the book.

Carryover Effects and Counterbalancing

The primary disadvantage of within-subjects designs is that they can result in carryover effects. A carryover effect is an effect of being tested in one condition on participants’ behavior in later conditions. One type of carryover effect is a practice effect , where participants perform a task better in later conditions because they have had a chance to practice it. Another type is a fatigue effect , where participants perform a task worse in later conditions because they become tired or bored. Being tested in one condition can also change how participants perceive stimuli or interpret their task in later conditions. This is called a context effect . For example, an average-looking defendant might be judged more harshly when participants have just judged an attractive defendant than when they have just judged an unattractive defendant. Within-subjects experiments also make it easier for participants to guess the hypothesis. For example, a participant who is asked to judge the guilt of an attractive defendant and then is asked to judge the guilt of an unattractive defendant is likely to guess that the hypothesis is that defendant attractiveness affects judgments of guilt. This could lead the participant to judge the unattractive defendant more harshly because he thinks this is what he is expected to do. Or it could make participants judge the two defendants similarly in an effort to be “fair.”

Carryover effects can be interesting in their own right. (Does the attractiveness of one person depend on the attractiveness of other people that we have seen recently?) But when they are not the focus of the research, carryover effects can be problematic. Imagine, for example, that participants judge the guilt of an attractive defendant and then judge the guilt of an unattractive defendant. If they judge the unattractive defendant more harshly, this might be because of his unattractiveness. But it could be instead that they judge him more harshly because they are becoming bored or tired. In other words, the order of the conditions is a confounding variable. The attractive condition is always the first condition and the unattractive condition the second. Thus any difference between the conditions in terms of the dependent variable could be caused by the order of the conditions and not the independent variable itself.

There is a solution to the problem of order effects, however, that can be used in many situations. It is counterbalancing , which means testing different participants in different orders. For example, some participants would be tested in the attractive defendant condition followed by the unattractive defendant condition, and others would be tested in the unattractive condition followed by the attractive condition. With three conditions, there would be six different orders (ABC, ACB, BAC, BCA, CAB, and CBA), so some participants would be tested in each of the six orders. With counterbalancing, participants are assigned to orders randomly, using the techniques we have already discussed. Thus random assignment plays an important role in within-subjects designs just as in between-subjects designs. Here, instead of randomly assigning to conditions, they are randomly assigned to different orders of conditions. In fact, it can safely be said that if a study does not involve random assignment in one form or another, it is not an experiment.

There are two ways to think about what counterbalancing accomplishes. One is that it controls the order of conditions so that it is no longer a confounding variable. Instead of the attractive condition always being first and the unattractive condition always being second, the attractive condition comes first for some participants and second for others. Likewise, the unattractive condition comes first for some participants and second for others. Thus any overall difference in the dependent variable between the two conditions cannot have been caused by the order of conditions. A second way to think about what counterbalancing accomplishes is that if there are carryover effects, it makes it possible to detect them. One can analyze the data separately for each order to see whether it had an effect.

When 9 Is “Larger” Than 221

Researcher Michael Birnbaum has argued that the lack of context provided by between-subjects designs is often a bigger problem than the context effects created by within-subjects designs. To demonstrate this, he asked one group of participants to rate how large the number 9 was on a 1-to-10 rating scale and another group to rate how large the number 221 was on the same 1-to-10 rating scale (Birnbaum, 1999). Participants in this between-subjects design gave the number 9 a mean rating of 5.13 and the number 221 a mean rating of 3.10. In other words, they rated 9 as larger than 221! According to Birnbaum, this is because participants spontaneously compared 9 with other one-digit numbers (in which case it is relatively large) and compared 221 with other three-digit numbers (in which case it is relatively small).

Simultaneous Within-Subjects Designs

So far, we have discussed an approach to within-subjects designs in which participants are tested in one condition at a time. There is another approach, however, that is often used when participants make multiple responses in each condition. Imagine, for example, that participants judge the guilt of 10 attractive defendants and 10 unattractive defendants. Instead of having people make judgments about all 10 defendants of one type followed by all 10 defendants of the other type, the researcher could present all 20 defendants in a sequence that mixed the two types. The researcher could then compute each participant’s mean rating for each type of defendant. Or imagine an experiment designed to see whether people with social anxiety disorder remember negative adjectives (e.g., “stupid,” “incompetent”) better than positive ones (e.g., “happy,” “productive”). The researcher could have participants study a single list that includes both kinds of words and then have them try to recall as many words as possible. The researcher could then count the number of each type of word that was recalled. There are many ways to determine the order in which the stimuli are presented, but one common way is to generate a different random order for each participant.

Between-Subjects or Within-Subjects?

Almost every experiment can be conducted using either a between-subjects design or a within-subjects design. This means that researchers must choose between the two approaches based on their relative merits for the particular situation.

Between-subjects experiments have the advantage of being conceptually simpler and requiring less testing time per participant. They also avoid carryover effects without the need for counterbalancing. Within-subjects experiments have the advantage of controlling extraneous participant variables, which generally reduces noise in the data and makes it easier to detect a relationship between the independent and dependent variables.

A good rule of thumb, then, is that if it is possible to conduct a within-subjects experiment (with proper counterbalancing) in the time that is available per participant—and you have no serious concerns about carryover effects—this is probably the best option. If a within-subjects design would be difficult or impossible to carry out, then you should consider a between-subjects design instead. For example, if you were testing participants in a doctor’s waiting room or shoppers in line at a grocery store, you might not have enough time to test each participant in all conditions and therefore would opt for a between-subjects design. Or imagine you were trying to reduce people’s level of prejudice by having them interact with someone of another race. A within-subjects design with counterbalancing would require testing some participants in the treatment condition first and then in a control condition. But if the treatment works and reduces people’s level of prejudice, then they would no longer be suitable for testing in the control condition. This is true for many designs that involve a treatment meant to produce long-term change in participants’ behavior (e.g., studies testing the effectiveness of psychotherapy). Clearly, a between-subjects design would be necessary here.

Remember also that using one type of design does not preclude using the other type in a different study. There is no reason that a researcher could not use both a between-subjects design and a within-subjects design to answer the same research question. In fact, professional researchers often do exactly this.

Key Takeaways

• Experiments can be conducted using either between-subjects or within-subjects designs. Deciding which to use in a particular situation requires careful consideration of the pros and cons of each approach.
• Random assignment to conditions in between-subjects experiments or to orders of conditions in within-subjects experiments is a fundamental element of experimental research. Its purpose is to control extraneous variables so that they do not become confounding variables.
• Experimental research on the effectiveness of a treatment requires both a treatment condition and a control condition, which can be a no-treatment control condition, a placebo control condition, or a waitlist control condition. Experimental treatments can also be compared with the best available alternative.

Discussion: For each of the following topics, list the pros and cons of a between-subjects and within-subjects design and decide which would be better.

• You want to test the relative effectiveness of two training programs for running a marathon.
• Using photographs of people as stimuli, you want to see if smiling people are perceived as more intelligent than people who are not smiling.
• In a field experiment, you want to see if the way a panhandler is dressed (neatly vs. sloppily) affects whether or not passersby give him any money.
• You want to see if concrete nouns (e.g., dog ) are recalled better than abstract nouns (e.g., truth ).
• Discussion: Imagine that an experiment shows that participants who receive psychodynamic therapy for a dog phobia improve more than participants in a no-treatment control group. Explain a fundamental problem with this research design and at least two ways that it might be corrected.

Birnbaum, M. H. (1999). How to show that 9 > 221: Collect judgments in a between-subjects design. Psychological Methods, 4 , 243–249.

Moseley, J. B., O’Malley, K., Petersen, N. J., Menke, T. J., Brody, B. A., Kuykendall, D. H., … Wray, N. P. (2002). A controlled trial of arthroscopic surgery for osteoarthritis of the knee. The New England Journal of Medicine, 347 , 81–88.

Price, D. D., Finniss, D. G., & Benedetti, F. (2008). A comprehensive review of the placebo effect: Recent advances and current thought. Annual Review of Psychology, 59 , 565–590.

Shapiro, A. K., & Shapiro, E. (1999). The powerful placebo: From ancient priest to modern physician . Baltimore, MD: Johns Hopkins University Press.

Research Methods in Psychology Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Laboratory Experiments

Last updated 22 Mar 2021

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Experiments look for the effect that manipulated variables (independent variables, or IVs) have on measured variables (dependent variables, or DVs), i.e. causal effects.

Laboratory experiments pay particular attention to eliminating the effects of other, extraneous variables, by controlling them (i.e. removing or keeping them constant) in an artificial environment. This makes it more likely for researchers to find a causal effect, having confidence that no variables other than changes in an IV can affect a resulting DV. Laboratory experiments are the most heavily controlled form of experimental research.

Participants can also be randomly allocated to experimental conditions, to avoid experimenter bias (i.e. the experimenter cannot be accused of choosing who will be in each experimental condition, which could affect the results).

Evaluation of laboratory experiments:

- High control over extraneous variables means that they cannot confound the results, so a ‘cause and effect’ relationship between the IV and DV is often assumed.

- Results of laboratory experiments tend to be reliable, as the conditions created (and thus results produced) can be replicated.

- Variables can be measured accurately with the tools made available in a laboratory setting, which may otherwise be impossible for experiments conducted ‘in the field’ (field experiments).

- Data collected may lack ecological validity, as the artificial nature of laboratory experiments can cast doubt over whether the results reflect the nature of real life scenarios.

- There is a high risk of demand characteristics, i.e. participants may alter their behaviour based on their interpretation of the purpose of the experiment.

- There is also a risk of experimenter bias, e.g. researchers’ expectations may affect how they interact with participants (affecting participants’ behaviour), or alter their interpretation of the results.

• Laboratory Experiment

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Example Answers for Research Methods: A Level Psychology, Paper 2, June 2019 (AQA)

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