Applied Statistics Using SPSS, STATISTICA, MATLAB and R

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c. The comparison between hospital 3 versus the others uses the assignment rule
for merged groups already explained in 4.5.2.2.
d. The comparison between all hospitals, for category 1 of APCLASS, uses two
independent contrasts. These are tested simultaneously, representing an
exhaustive set of contrasts that compare all levels of HOSP. Category 0 of
APCLASS is removed from the analysis by assigning a zero coefficient to it.
Table 4.23. Contrast coefficients and significance for the comparisons described in
Example 4.21.
Contrast (a) (b) (c) (d)
Description
APCLASS 0
vs.
APCLASS 1
HOSP 2
vs.
HOSP 3
HOSP 3
vs.
{HOSP 1, HOSP 2}
HOSP coef. 1 1 1 0 1 −1 1 1 −2
HOSP
for
APCLASS 1
1 0 −1
0 1 −1
APCLASS coef. 1 −1 1 1 1 1 0 1
p 0.00 0.00 0.29 0.00
Estimated Marginal Means
80
70
60
50
40
30
1
4.5 Inference on More than Two Populations
HOSP
2
3
APCLASS
Figure 4.20. Plot of estimated marginal means for Example 4.20.
SPSS and STATISTICA provide the possibility of testing contrasts in multi-way
ANOVA analysis. With STATISTICA, the user fills in at will the contrast
coefficients in a specific window (e.g. click Specify contrasts for LS
means in the Planned comps tab of the ANOVA command, with
HOSP*APCLASS interaction effect selected). SPSS follows the approach of
computing an exhaustive set of contrasts.
0
1