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Biostatistics

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360 CHAPTER 8 ANALYSIS OF VARIANCE<br />

TABLE 8.5.2 Data of Table 8.5.1 Altered to Show<br />

the Effect of One Type of Interaction<br />

Factor B—Drug Dosage<br />

Factor A—Age j ¼ 1 j ¼ 2 j ¼ 3<br />

Young ði ¼ 1Þ m 11 ¼ 5 m 12 ¼ 10 m 13 ¼ 20<br />

Old ði ¼ 2Þ m 21 ¼ 15 m 22 ¼ 10 m 23 ¼ 5<br />

Reduction in reaction time<br />

30<br />

Age<br />

25<br />

20<br />

a 1<br />

15<br />

10<br />

5<br />

a 2<br />

0<br />

b 1 b 2 b 3<br />

Drug dosage<br />

FIGURE 8.5.2 Age and drug effects, interaction present.<br />

Reduction in reaction time<br />

30<br />

25<br />

20<br />

15<br />

10<br />

5<br />

0<br />

a 1 a 2<br />

Age<br />

Drug dosage<br />

b 1<br />

b 2<br />

b 3<br />

The presence of interaction between two factors can affect the characteristics of the<br />

data in a variety of ways depending on the nature of the interaction. We illustrate the effect<br />

of one type of interaction by altering the data of Table 8.5.1 as shown in Table 8.5.2.<br />

The important characteristics of the data in Table 8.5.2 are as follows.<br />

1. The difference between means for any two levels of factor B is not the same for both<br />

levels of factor A. We note in Table 8.5.2. for example, that the difference between<br />

levels 1 and 2 of factor B is 5 for the young age group and þ5 for the old age group.<br />

2. The difference between means for both levels of factor A is not the same at all levels<br />

of factor B. The differences between factor A means are 10, 0, and 15 for levels 1, 2,<br />

and 3, respectively, of factor B.<br />

3. The factor level curves are not parallel, as shown in Figure 8.5.2.<br />

When population data exhibit the characteristics illustrated in Table 8.5.2 and<br />

Figure 8.5.2, we say that there is interaction between the two factors. We emphasize<br />

that the kind of interaction illustrated by the present example is only one of many types of<br />

interaction that may occur between two factors.<br />

&<br />

In summary, then, we can say that there is interaction between two factors if a change<br />

in one of the factors produces a change in response at one level of the other factor different<br />

from that produced at other levels of this factor.<br />

Advantages<br />

The advantages of the factorial experiment include the following.<br />

1. The interaction of the factors may be studied.<br />

2. There is a saving of time and effort.

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