Information Technology Reference
In-Depth Information
Figure 8.22
The Process Flow window after importing the data set.
code that we have named subid . Next are the independent variables. We
have given them arbitrary codes (values) to represent our categories. For
gender , females are coded as 1 and males are coded as 2; for reside , large
city, small town, and rural community are coded as 1, 2, and 3, respectively.
The final column holds the dependent variable for the analysis. We have
named this variable lonely . In this column are the scores on the loneliness
inventory for each participant. As described in Appendix B, import this
data into SAS Enterprise Guide . When you have imported the data file,
your window should resemble the one shown in Figure 8.22.
8.13.2 STRUCTURING THE ANALYSIS
Select Analyze ANOVA Linear Models . The window for this pro-
cedure opens on the Task Roles tab; this is highlighted in the navigation
panel in the left portion of the window shown in Figure 8.23. At the top
of the panel labeled Linear Models Task Roles there is already a place for
a dependent variable being specified. Highlight lonely anddragittothe
icon for Dependent variables (you can also highlight lonely , click the
right-facing arrow, and select Dependent variables as the destination).
Then drag gender and reside to the icon for Classification variables (or
highlight them, click the arrow, and select your destination). When fin-
ished, your screen should look similar to the screen shown in Figure 8.24.
Click on the Model tab. The variables group and reside appear in the
Class and quantitative variables panel. Highlight gender and click the
Main bar to place gender in the Effects panel. Then do the same with
reside . Finally, highlight gender and, while depressing the Control key,
highlight reside ; both variables should now be highlighted. Clicking the
Search WWH ::




Custom Search