Lecture 8 Show
The Concept of Repeated Measures or Within Subjects The concept of repeated measures is pretty easy at first, but then starts to seem more complicated as you go along. Till now, we have compared two groups on a single measure. For instance, comparing two experimental groups on arthritis symptoms. That situation is often called "between subjects" because some subjects in the experiment received the new drug and some received the old drug. Comparison of symptoms was made between different subjects. Experiments are also conducted where the same person receives both drugs at different times. For example, a single patient might start the study taking aspirin, then after two weeks, the new drug is started. Symptoms in the first phase of the study are counted and symptoms in the second phase are counted. This is called repeated measures, because the measure is repeated for each subject. To analyze this type of study, a special type of statistical test is needed--the within-subjects t-test. "Within" is used because the measure (or measures) being examined is said to be nested within each subject. The term "within subjects" is slightly more general than "repeated measures," because this type of t-test is used in cases other than the repeated measures situation. For instance, one could compare two different measures. A standardized math test might be compared to a standardized verbal test, with the hypothesis that the students in the sample have stronger verbal skills. Another use of the within-subjects t-test is when subjects are linked or paired together in some way. The best example of this is twin studies. Monozygotic twins are compared on alcoholism or some other dimension. In this case, drinking behavior would be analyzed as if there were repeated measurements of the same person. Each twin pair is considered to be the same in some sense. There are several other ways we can link pairs of subjects though, such as married couples, siblings, or participants matched on age or some other dimension. If participants were matched on age, all participants are first ranked according to their age, then pairs of participants of the same (or very close) age are split into two groups, one member or each pair assigned to each group. Each pair is then kept linked together or "yoked." So, there are several terms that might be used for this type of test: within-subjects t-test, paired t-test, matched pair t-test, or repeated measures t-test. All refer to the same type of test in which pairs of scores are linked together and compared. Example
We want to test whether the new scheduling system will significantly increase the number of visits possible. To do this, we need to test whether the increase in visits is simply a chance occurrence or not. Steps
Computations
I'll calculate the variance of the difference both ways, but you don't have to. Now, the standard error of the differences. And the t value: To see if this computed value is significant, we should compare it to the tabled value (Table E), looking up under d.f. = n - 1 = 6. The critical value to exceed is t.975 = 2.4496. Because our calculated value of t for the sample, 3.61, is larger than 2.4496 found in the table, we decide our difference is large enough and therefore significant. We reject H0 which stated that there was no difference between before and after measurements. Interpretation The unique thing about this test is that we compare every individual's score to his/her other score, by subtracting the second score from the first (). Then we find the average of that. In the between-groups t-test, we computed the mean of score for one group and then compared it to the mean score of the other group. With the within-subject approach differences are found first, then the average, and with the between-subjects we find the average first, then the difference. Advantages of the Within-subjects t-test. Because each person (or pair) has his or her own control, we will have less overall variation in the sample than if we compare different people in two different groups. And because we can reduce the overall variation, the estimate of sampling variability will be smaller (remember that is estimated using the variability in the sample, ). In other words, will generally be smaller than . In general, within-subjects tests designs have this advantage over the between-subjects designs. Within -subjects designs have more power to detect significance because there is less variability. If it is ethically or methodologically possible to do, an experiment with a within-subjects design is more powerful and economical than a between-subjects experiment. For an example SPSS output click here. What is it called when the same group of subjects is used for each condition?Repeated Measures design is an experimental design where the same participants take part in each condition of the independent variable. This means that each condition of the experiment includes the same group of participants. Repeated Measures design is also known as within groups, or within-subjects design.
What does between participants mean in a between participants experiment?Between-subjects (or between-groups) study design: different people test each condition, so that each person is only exposed to a single user interface. Within-subjects (or repeated-measures) study design: the same person tests all the conditions (i.e., all the user interfaces).
What is a research design in which different participants are observed at one time in each group?A research design in which different participants are observed one time in each group of a research study is called: between-subjects design.
Which of the following research designs involves measuring the same group of participants in two different treatment conditions?A within-subjects design is also called a dependent groups or repeated measures design because researchers compare related measures from the same participants between different conditions.
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