Factorial ANOVA


To conduct a Factorial ANOVA one only need extend the logic of the oneway design. Table 13.2 presents the data for a 2 by 5 factorial ANOVA. The first factor, AGE, has two levels, and the second factor, CONDITION, has five levels. So, once again each observation can be uniquely coded.

AGECONDITION
Old = 1Counting = 1
Young = 2Rhyming = 2
Adjective = 3
Imagery = 4
Intentional = 5

For each pairing of AGE and CONDITION, there are 10 observations. That is, 2*5 conditions by 10 observations per condition results in 100 observations, that can be coded as follows. [Note, that the names for the factors are meaniful.]


AGECONDITIOScores
119
118
116
1......
117
127
129
126
1... ...
1......
1......
1510
1519
1......
1511
218
216
214
2......
217
2210
227
228
2... ...
2......
2......
2521
2519
2......
2521

Examine the table carefully, until you understand how the coding has been implemented. Note: one can enhance the readability of the output by using Value Labels for the two factors.



To compute the relevant statistics - a simple approach,

As noted earlier, the analysis that was just conducted is the simplest approach to performing a Factorial ANOVA. If one uses [Statistics => General Linear Model => GLM - General Factorial...], then more options become available. The specification of the Dependent and Independent factors is the as the method used for the Simple Factorial analysis. Beyond that, the options include, The use of the GLM - General Factorial procedure offers a great deal more than the Simple Factorial. Depending on your needs, the former procedure may provide greater insight into your data. Explore these options!

Higher order factorial designs are carried in the same manner as the two factor analysis presented above. One need only code the factors appropriately, and enter the corresponding observations.

Repeated measures designs will be discussed in the next section.