An independent measures design is a type of method used during a psychology experiment that involves two or more separate groups, each containing different individuals, where each participant only takes part in each condition once.
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See also Repeated measures design.
Advantages of independent measures design
The One advantage is that more participants are used in the overall experiment, compared to repeated measures design, increasing the external validity. Another advantage is that independent measures only requires one set of participants and one test for each condition of the independent variable. This saves time and is a lot quicker than using a repeated measures design.
Disadvantages of independent measures design
One of the main disadvantages of using independent measures design is the potential for error resulting from the individual differences of the participants, because they do not match those in other groups, which would affect the results and therefore the internal validity (and reliability). The participants no longer become a control variable because you are using two different groups of people. It could be said that the results turned out the way they did because of other factors present to each group before the experiment even took place.
For Example in group A the average IQ is 120 in group B the average IQ is 118, this is a variable, or individual difference that the experimenter is not aware of. So group A might perform better on average, not due to the independent variable being changed but the individual differences in participants.