How to Calculate the Bonferroni Correction The calculation for this post-hoc test is actually very simple, it’s just thealpha level(α) divided by the number of tests you’re running. Sample question:A researcher is testing 25 different hypotheses at the same time, using a critical value of...
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0.01 according to Bonferroni correction was considered as significant. Results We included a total of 225 patients. By counselling the physicians, we reduced the number of patients with problems from 55% to 43% (control [i] vs. first intervention [ii], n.s.). With additional feedback to ...
Conducting multiple subgroup analyses increases the likelihood of finding false positives due to chance. To mitigate this, apply appropriate statistical adjustments (e.g., Bonferroni correction) to control the overall Type I error rate. Adequate Sample Size ...
Note: When the ANOVA is significant, post hoc tests are used to see differences between specific groups. post hoc tests control the family-wise error rate (inflated type I error rate) due to multiple comparisons. post hoc tests adjust thepvalues (Bonferroni correction) or critical value (Tukey...
After Bonferroni correction for multiple comparisons (correcting for the seven correlations), all reported significant correlations remained significant apart from the positive association between valuing happiness and PANAS. Table 1 Means, standard deviations, and correlations between valuing happiness and ...
Moreover, tests of between-subject found a significant difference in emotion contagion (p < .001), attention to others’ feelings (p < .001) and prosocial actions (p < .001). Bonferroni’s post-hoc highlighted that children with DS were perceived as having more emotion ...
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Because Excel doesn’t provide post hoc tests, you can perform a simple version of it using the Bonferroni correction and a series of 2-sample t-tests. For the Bonferroni correction, take your significance level and divide it by the number of comparisons. If you compare all possible pairs ...
The Bonferroni test, also known as "Bonferroni correction" or "Bonferroni adjustment" suggests that thep-valuefor each test must be equal to its alpha divided by the number of tests performed. The Bonferroni test is a multiple-comparison correction used when several dependent or independent statisti...