If you’re doing a study using two or more groups, you’ve got two options: You can use different people in each group (between participants design), or you can use the same participants in each group (within participants design). There are pros and cons to each.
Say I’m an office manager and I want to measure the effect of distraction on workplace performance. My workers always have that damned radio playing all those cheesy love songs, and I think it’s distracting them and costing me valuable profit. So I hire a researcher to find out for sure.
He might use a between participants design. On one floor of my office he bans the radio. On another floor, he let’s them carry on as usual. At the end of the week, we work out which floor got the most work done. Pretty simple.
Or, he might use a within participants design. He only looks at one floor. For a week he measures their workrate while the radio is there, then the week after he takes it away and measures workrate again.
What’s the best way?
There’s no right or wrong answer. If he used a between participants design, he’s got different people on each floor. Maybe one floor is populated by people who are better workers than the other floor. To truly test the effect of the radio, and nothing else, the conditions – and the people – in the test would have to be exactly the same. Normally in psychology, researchers try to get large numbers of people in each group, and assign people randomly to each one. That way it’s expected that, since most human traits fall on a normal distribution, the groups will be pretty similar to each other on average.
But to get them exactly the same, you’d have to use the same people! That’s a within participants design. This brings it’s own problems with it. In this particular example, there might be temporal effects – differences in the environment week by week. For instance, maybe there were an unusually high number of birthdays in the office on the second week, and they went out celebrating a few times, leaving them tired at work. Or maybe on the first week, they were a bit nervous about having a researcher watching over them, but by the second one they had gotten over it.
Temporal effects aren’t limited to within participants designs of course – in a between participants design you might test the groups at different times; although you should not do this unless you have no other choice, to avoid these temporal effects.
Within participants designs are also vulnerable to something called practice effects. If I’m measuring the effect of caffeine on some cognitive ability, such as working memory, I might test people when they first step into the lab, then give them a triple espresso, and test them again.
Is this a between or within participants design? It’s within participants – testing the same people twice. But, the second time they do the test they know what to expect; they have had a little practice. So they might improve on the second test purely through this practice effect, rather than the caffeine.
Alternatively, maybe the results were influenced in the opposite direction – maybe they got bored of doing the test twice and didn’t put as much effort in the second time around.
There’s a way of getting around this – counterbalancing. You split the sample in two, and half of them would get the espresso before the first test, while the other half would get it before the second test. In this case you’d have to leave a few hours between tests so that the caffeine wears off, but both conditions – with caffeine and without caffeine – would be equally susceptible to practice effects, so we can be more certain that any difference is due to the effect of the caffeine.
Once more, just to clarify
In a between participants design, a given participant is allocated to one group or the other, but not both.
In a within subjects design, a given participant is allocated to both groups.
Advantages of between participants design:
Help to avoid practice effects and other ‘carry-over’ problems that result from taking the same test twice.
Is possible to test both groups at the same time.
Disadvantages of between participants design:
Individual differences may vary between the groups
Vulnerable to group assignment bias (though you would use random assignment wherever possible to compensate)
Advantages of within participants design:
Half the number of participants need to be recruited
They offer closer matching of the individual differences of the participants.
Disadvantages of within participants design:
Practice and other ‘carry-over’ effects may contaminate the results (though you would use counterbalancing where possible to compensate)
Visualising this in SPSS
When you’re putting data into SPSS, a row always indicates a single participant. Data from two different participants will never appear on the same row. Therefore, in a within participants design, our coffee experiment would have two columns for our data – one for with caffeine, one for without.
But, if we had used a between participants design, we would have ONE column for the data, plus another column saying which group that participant was in.
Between participants is also known as independent measures design, or between subjects design.
Within participants is also known as repeated measures design, or within subjects design.
Are you finding the stats section of your course a little difficult? It’s hard to understand at first, but I’ve explained the bulk of what you need to know in plain English, in the study guide. Have a look.