Clinical Biochemistry of Domestic Animals (Sixth Edition) - UMK ...

22
Chapter | 1 Concepts of Normality in Clinical Biochemistry
Estimated Marginal Means
1. Age
Estimates
Measure: count
95% Confidence Interval
Age
Mean Std. Error Lower Bound Upper Bound
infant 53.333 .540 52.089 54.578
adult 49.067 .540 47.822 50.311
2. Cocktail
Measure: count
Estimates
95% Confidence Interval
Cocktail
Mean Std. Error Lower Bound Upper Bound
1 42.300 1.138 39.676 44.924
2 51.100 .557 49.816 52.384
3 60.200 .771 58.421 61.979
Measure: count
Pairwise Comparisons
(I) cocktail (J) cocktail Mean
Difference
(IJ)
95% Confidence Interval
for Difference a
Std. Error Sig. a Lower Bound Upper Bound
1 2 8.800* 1.517 .001 13.374 4.226
3 17.900* 1.606 .000 22.744 13.056
2 1 8.800* 1.517 .001 4.226 13.374
3 9.100* .640 .000 11.031 7.169
3 1 17.900* 1.606 .000 13.056 22.744
2 9.100* .640 .000 7.169 11.031
Based on estimated marginal means
* The mean difference is significant at the .05 level.
a Adjustment for multiple comparisons: Bonferroni.
FIGURE 1-15 (Continued).
as those given previously for the example of the basic
repeated measures design with the following additions:
1. In the Repeated Measures dialog box, age is
added as a between subjects factor by moving “ age ” into
the Between-Subjects Factor(s): box.
2. In the Repeated Measures: Options dialog box,
both the repeated measures factor, here cocktail , and the
between subjects factor, here age , are moved from the
Factor(s) and Factor Interactions: box to the Display
Means for: box for requesting options such as the display
of descriptive statistics.
3. For between subject factors having more than 2
categories, pairwise multiple comparisons of means can
be obtained by hitting the Post-Hoc... tab, which opens the
Repeated Measures Post Hoc Multiple Comparisons
for Observe... dialog box. In this dialog box all desired
between subject factors can be moved from the Factor(s):
box to the Post Hoc Test for: box and the desired pairwise
multiple comparisons procedure(s) selected.
A partial printout of the SPSS output for the example
is presented in Figure 1-15 . Cocktail ( COCKTAIL ),
the within subject main effect, is highly significant
( p 0.0005), age ( AGE ), the between subject main effect,
is also highly significant ( p 0.001), but the interaction
between cocktail and age ( COCKTAIL * AGE ) is nonsignificant
( p 0.177).