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