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However, doing the same tasks repeatedly can cause problems when analysing test effects. The participants might get used to this type of test after doing it a few times. Also, repeating the same thing can make them bored and tired, affecting the research quality. A way to avoid these issues is by using an independent groups design (IGD).
- We will start by exploring the independent group design definition and how the experimental design: independent groups, is often used in research.
- Next, we will look at some independent group design examples in the context of psychological research.
- Finally, the advantages of independent group design and limitations of independent group design will also be discussed.
What are Independent Groups Designs?
An independent groups design is an experimental design where different participants are used in each condition in an experiment. Participants are randomly allocated.
Fig. 1 - Independent group designs use different participants in each condition.
Independent Groups Design Definition
Independent group design (IGD) is an experimental design whereby different participants are used for each experimental condition. The researcher exposes separate sets of randomly allocated participants to different experimental conditions.
A hypothetical study compared the results to see how one group (the experimental sleep-deprived group) performed compared to another (the control, well-rested group) in a memory test.
In this experimental design, different participants participated in different conditions, i.e. the sleep-deprived versus well-rested group. And this characteristic is what makes this study an independent group design. The defining characteristic of this experimental design is that each group uses different participants.
Experimental Design: Independent Groups
An experimental design is a research method that aims to test a hypothesis and ensure that research is executed in a controlled and scientific manner; this leads to collecting representative data and drawing conclusions. If the researchers follow the appropriate steps and implement the necessary measures, the results may be considered valid and reliable.
Remember, an experimental design measures the independent variable's effect on the dependent variable.
In an independent group design, think of an experimental and a controlled group. For the experimental group of individuals, there is a manipulation of the independent variable.
To remember these terms, you can think of them as 'cause' and 'effect' values.
The independent variable acts as the 'cause' factor in the experiment. It is the manipulated variable that is independent of other variables.
The dependent variable's value is predicted to depend on the independent variable's changes. It is the 'effect' factor. It is the variable being measured.
Independent group design differs from a repeated group design, which uses the same individuals on two or more different occasions for different experimental conditions. In repeated measures designs, all participants do each task.
Fig. 2 - Scientific research involves assigning participants to experimental conditions; an example is the independent group design.
Independent Group Design: Psychology Research Examples
Several study examples present what makes up an independent group design. In the following text, we will present two.
Let's consider a study on sleep that explored how different amounts of sleep affect people's reaction times. The hypothetical study recruited two groups of ten different individuals.
Whilst one group had ten hours of sleep per night, the other group had three; this means that the independent variable will be the amount of sleep (the manipulated variable).
The dependent variable (the measured variable) was their recorded reaction time.
| The hypothesis | less sleep causes slower reaction times |
| The independent variable | the amount of sleep groups 1 and 2 had |
| The dependent variable | the reaction time of individuals in groups 1 and 2 |
One group had ten hours of sleep, whilst the other had three, and different participants were tested in each condition, so the experimental design was an independent group design.
A second theoretical study used an independent group design to test the potential side effects of a prescription drug. Participants were split into two groups, group A and group B.
Group A was given the drug, and group B was given a 'placebo' drug (one with no active ingredients). From this research, we would expect no side effects in Group B as no active ingredients mean that the medication will not affect them.
In this case, the independent variable is the drug, and the dependent variable is the possible side effects of the drug.
| The hypothesis | drug X causes side effects Y |
| The independent variable | the drug taken by the individuals |
| The dependent variable | the potential side effect |
Group A is testing the drug and will not take the placebo. Group B is not testing the drug and will take the placebo. Each group experiences different testing conditions, so we can attribute differences in the results to the specific manipulation of the independent variable, that is, taking and not taking the drug. This is one of the many benefits of using this experimental design compared to others.
There are three different types of experimental designs; the independent group design is one of these. Sometimes researchers use others; the type used depends on how the research method will allocate participants to experimental conditions.
The repeated measure design is used when the same participants are used in both experimental conditions. And a matched-pairs design is used when participants are allocated to groups, and each group pair is matched based on a key characteristic.
Advantages of Independent Groups Design
There are both advantages and disadvantages to using an independent group design to test a hypothesis.
However, sometimes researchers must use an independent group design because it may not be possible to test different participants in each condition.
Imagine a study testing the effectiveness of a revision plan. If we tested different participants who received the revision plan to those who didn't, the results might be due to participant variants.
Instead, a researcher may compare the participants' test scores before and after using the revision plan. As the study uses the same participant in each condition, it is classed as a repeated measures design, which accounts for individual differences.
A key advantage to independent group designs is that there are no order effects. Since different participants are exposed to each condition, the order in which they are done does not affect the outcome. Participants are more likely to act accordingly. They cannot practice and get better. They also will not become fatigued or bored.
In repeated measure designs, order effects such as the practise effect or fatigue/boredom effect can influence the results of the experiment and, therefore, could decrease the accuracy of the data.
Another advantage is that, since more participants are required because each can only belong to one group, the results have increased external validity.
External validity refers to the extent to which the findings of a study can be generalised to other people, situations, and environments.
The more people involved, the more likely the differing representation and, thus, the higher the external validity.
Finally, there is always the benefit of both time, effort, and money saved because both groups of participants can be tested simultaneously.
Limitations of Independent Groups Design
Because there are two groups of different individuals, more participants are needed. This may outweigh the benefit of testing both groups because, for instance, more equipment may be required for more individuals, making independent group design less economical.
Participant variables exist. Since there are different groups of individuals, it is difficult to ensure that the differing results are because of the manipulated independent variable - the changes in the DV observed may be because of participant variables.
Considering the first example above, which shows the effect of reaction time on sleep, the general prediction is that those in the group limited to three hours have slower reaction times.
But what if over half of these individuals had personal, participant-specific conditions that slowed their reaction time regardless of how many hours they'd slept?
For instance, poor diets or less dexterity/ability to react overall as they have never experienced the conditions before, whereas someone who plays sports or video games may have better reaction times, affecting the recording of the results.
This is known as a participant variable.
Another example may be that participants in one condition may be more intelligent (with higher IQs) than others.
Some variables are not always confounding because they do not matter as much (it depends on whether or not they are relevant to the outcome). But, if they do matter, this may lead to invalid conclusive data.
So, how can we lower the chance of participant variables?
The answer is random sampling. Although this does not entirely eliminate the issue, it reduces the chances of participant variables confounding the experiment results.
Random sampling means that each member of a population has an equal chance of being selected through random list generators on computers or placing names in a container and drawing them out randomly.
Random sampling is advantageous for independent group design experiments because of the unbiased selection. This increases the chance of having a more representative sample of participants, thus increasing the results' external validity.
Independent Group Design - Key takeaways
- An independent group design is an experimental design where different participants are used in each condition in an experiment. Participants are randomly allocated.
- We can think about one group as the experimental and the other as the controlled group. The difference is the changing of the independent variable, the 'cause' factor of the experiment (for example, the amount of sleep the individuals get).
- The main advantages of independent group design are that there are no order effects, there is increased external validity, and it can save time, effort, and money because both groups can go through testing simultaneously.
- There are also disadvantages to using independent group designs - more participants are needed (which is less cost-effective), and there is the chance of participant variables tampering with the validity of results.
- One way to overcome key disadvantages is to try and reduce costs in other ways and use random sampling to reduce bias.
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Frequently Asked Questions about Independent Group Design
What is independent group design in research?
An independent groups design is an experimental design where different participants are used in each condition in an experiment. Participants are randomly allocated.
What is an example of independent groups design?
An example of an independent group design is testing the hypothesis that less sleep causes slower reaction times. The researcher can divide the participants into two groups to test this hypothesis – one group getting ten and the other three hours of sleep.
The independent variable is the amount of sleep, and the dependent variable is the reaction time.
How do you overcome the disadvantages of independent group design?
You can overcome the disadvantages by using random sampling. This introduces an unbiased selection process which increases the likelihood of having a representative sample and increases the external validity of the results.
Are independent group design and quasi-experiment the same?
A quasi-experiment design differs from an independent group design because the former does not depend on random sampling or the assignment of individuals. In quasi-experiment, subjects are specifically assigned to their groups based on selective criteria.
What are the three different types of independent group designs?
The three different types of independent group designs are random group designs, matched group designs, and natural group designs.
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