Given Hapunda

160 6. Options in the lower right corner to open the One-Way ANOVA: 7. Options dialogue box. 8. Check Homogeneity of variance test. 9. Click Continue to return to the One-Way ANOVA dialogue box. 10. Click OK at the bottom of the One-Way ANOVA dialogue box to run the one-way ANOVA. Table 5: ANOVA Test Results Output ANOVA Malaria cases at baseline Sum of Squares df Mean Square F Sig. Between Groups 11.267 2 5.633 3.911 .022 Within Groups 197.333 137 1.440 Total 208.600 139 The results of the overall F test in the ANOVA summary table can be examined to determine whether group means are statistically different. The overall F test is significant in the above output (i.e., p value < 0.05), and it indicates that means between groups are not equal for the number of malaria cases as a function of the residence. To report the ANOVA results, you indicate the main statistical output that will aid with the interpretation and in this case, you indicate F (2, 137) = 3.911, p < .05. Since the ANOVA in the table above confirms that there was a significant difference among the three residencies, in its current form, it does not tell us which of the residencies differ in the malaria cases. To achieve this, multiple comparisons also referred to as planned or post-hoc comparison tests need to be performed to tell us more on which residencies differed significantly. Examples in SPSS include; LSD, Sidak, Scheffe, Duncan, Dunnett, SNK, Bonferroni, and more… These post-hoc comparisons are often selected based on the rationale they hold for performing the comparisons.