Psychology -> Ways to minimise the effects of extraneous variables; a brief overview of three experimental designs
Ways to minimise the effects of extraneous variables; a brief overview of three experimental designs
Matched - Subjects design
Independent - groups design
Repeated - Measures design
In any experiment, the goal of the researcher is to be able to confidently conclude that the observed effect was caused by the independent variable alone. However, the difficulty arises when the dependent variable can be influenced by variables other than the independent variable.
Variables, other than the independent variable, which may influence the dependent variable are called extraneous variables. Extraneous variables have the effect of confounding the results in an experiment and the researcher can no longer draw conclusions regarding the causal relationship that exists between the independent variable and the dependent variable.
In order to minimise the effects of extraneous variables, researchers may choose the following experimental designs:
In order to control for variations in subject characteristics (which may influence the dependent variable), a within-subjects design may be used called a repeated-measures design. This is where the subjects within an experiment are tested or measured more than once, i.e. they are repeatedly measured. The same subjects are used in each condition, receiving all levels of the independent variable thereby guaranteeing equivalence of groups at the beginning of the study.
For example, subjects may be given a pre-test and then asked to complete a post-test. In this way, the subject characteristics remain constant. Another example is if a researcher wanted to study attention span for complex and simple visual stimuli. The researcher may test the same children who would be exposed to both the complex and the simple visual stimuli conditions. The attention span of all children would be tested under each of the two conditions, hence the subjects are repeatedly measured. This ensures that the two groups are equivalent in subject characteristics, minimising the influence of extraneous variables.
As well as utilising a repeated-measures design to minimise the effects of extraneous variables, researchers often choose to conduct a matched-subjects design. A matched-subjects design also attempts to obtain equivalence between groups thus increasing the sensitivity of the experiment. It is where subjects are matched or equated on one or more variables (other than the independent variable) assumed to have an effect on the dependent variable. Then, whenever possible, the subjects are randomly assigned to conditions. In this way, the sensitivity of the experiment is increased.
For example, a researcher may identify the variable of subject intelligence as having an impact on the dependent variable. All the subjects would be matched on intelligence level, holding this variable constant and therefore controlling for it in all groups. The subjects would then be randomly assigned to experimental conditions.
A matched-subjects design can also mean that each subject has a matched subject in each of the other conditions so that the groups are correlated. Therefore, rather than using the same subjects in each condition as in the repeated-measures design, the matched-subjects design uses different subjects in each condition who have been matched as much as possible on identified variables.
This research design is also known as a between-subject design as it has different subjects in each group. The separate or independent groups of subjects receive different levels of the independent variable, so there is no chance of one treatment contaminating the other. In its simplest form, the experimental group receives the independent variable and the control group does not.
However, the independent-groups design has the potential of introducing variables other than the independent variable because of differences among the subjects in the groups. These extraneous variables may confuse the clear relationship between the independent variable and the dependent variable. Therefore, to minimise the confounding of subject characteristics with the independent variable, subjects need to be either randomly assigned to the different conditions or matched between groups on personal characteristics. These procedures ensure the formation of equivalent groups of subjects.