CSUF Department of Psychology
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Randomized Experiments

Experimental Design

Experimental design refers to the different ways of setting up a psychological experiment. There are two important general principles to remember about the process of experimental design. The first is that the primary goal of all experimental designs is to manipulate the independent variable while controlling extraneous variables. The second is that there are usually multiple ways to design an experiment to answer any particular research question, and allthough there are standards for judging one design to be better or worse than another, it is not always possible to say which design is "the best."

Randomized Experiment

A randomized experiment has a single independent variable with two or more levels that define the experimental conditions. For example, an experiment on the effect of noise on concentration might involve testing some subjects in a quiet condition and others in a noisy condition.  Noise level is the independent variable and it has two levels. The independent variable in a randomized experiment can also have more than two levels. For example, this same experiment could have three conditions: quiet, moderately noisy, and very noisy.

Note that conditions are sometimes referred to as "groups" (e.g., "the quiet group"), but this does not usually mean that all the subjects in a condition are tested at the same time in the same place.  Even if we tested one subject per day in the quiet condition for several days, we would still say that these subjects constituted the “quiet group."

A crucial feature of the randomized design is that subjects are assigned randomly to conditions.  This is referred to as the random assignment.  For the assignment of subjects to conditions to be considered truly random, two conditions must be met.

1) Each subject must have an equal chance of being assinged to each condition.  For example, for each subject, you might flip a coin.  If the coin lands heads, you assign the subject to the quiet condition; if it lands tails, you assign the subject to the noisy condition.  This would give each subject the same chance of ending up in, say, the quiet condition as ending up in the noisy condition.

2) Each subject’s chances of ending up in one condition or the other must be independent of the chances of other subjects.  For example, it is not random assignment if you split a group into those on the left half of the room and those on the right, and then you flip a coin to determine that those on the left will be in Condition A and those on the right in Condition B.  This is because each subject’s chances of being in one condition or the other are linked to those of the other subjects.  A subject on the left side of the room is guaranteed to be assigned to the same condition as the other subjects on the left side of the room (and the opposite condition as the subjects on the right side of the room).  Their chances are not independent.

Why Use Random Assignment?

Although it may not be obvious at first, random assignment is a way of controlling extraneous variables.  This is because it tends to produce groups that are fairly similar on average.  For example, imagine that you randomly assign 100 subjects to either a quiet or noisy condition so that there are 50 subjects in each. You can be pretty sure that there are roughly the same number of men and women in the two conditions, that their average IQ is roughly the same, that their average hearing sensitivity is roughly the same, and so on.  For this reason, any differences between the two groups on the dependent variable can be attributed to the independent variable, and not to anything else.

Not using random assignment, however, can result in confounding variables.  Imagine, for example, that we assign subjects sitting on the left half of the room to the quiet condition and subjects sitting on the right half of the room to the noisy condition. The problem here is that we run the risk that there is some difference between these two groups--left-side sitters and right-side sitters--that might affect our results.  For example, if the door is on the left side of the room, perhaps the more motivated students arrive early and sit on the left side, while the lazy slackers arrive late and sit on the right.  In fact, there might be all sorts of differences between left-side sitters and right-side sitters that we cannot even think of.  We sidestep this problem completely, however, by using random assignment.

Does random assignment absolutely guarantee that the groups will be similar in terms of all important extraneous variables?  No.  For example, it would still be possible for most of the more intelligent subjects in the sample might end up in the quiet condition, while most of the less intelligent ones ended up in the noisy condition.  But with a large enough sample size, it is very unlikely.  Also, if this does happen, it would be considered a fluke and not the fault of the researcher.

Some Other Considerations

Getting Equal Group Sizes

It is generally considered desirable to have the same number of subjects in each condition, but true random assignment is unlikely to result in exactly the same number. How do we deal with this? One way would be to flip a coin to assign the first subject to one condition, then assign the next subject to the other condition, then flip a coin to assign the third subject to one condition, then assign the next subject to the other condition, and so on.  Note that technically this violates the independent-chances criterion described above, but it does so in a way that would be unlikely to result in differences between conditions.

When to Use Random Assignment  

It is usually inconvenient to be flipping coins at the time of the experiment, which is why researchers generally create a randomization scheme ahead of time.  For example, before you actually do your experiment, you might flip a coin to determine that the first subject will be in the quiet condition, so the second will be in the noisy condition, and so on.  You can do this to create a complete list of conditions for however many subjects you plan to test, and then you can assign each subject to the next condition on the list as you encounter them.

How to Use Random Assignment

Flipping a coin is only one way to randomly assign people to groups, which works well when there are only two groups.  But you can use any method that accomplishes the same thing.  You can roll a die, draw slips of paper out of a hat, consult a list of random numbers, or use a random number generator.  For example, for an experiment with four groups, you could generate a random number between 0 and 1 for each subject.  If it is less than .25, they go into Condition A; if it is from .25 to .50, they go into Condition B; and so on. Another convenient program will generate a randomized list for any number of conditions and subjects.