Contents
What does a Dunn test show?
What is Dunn’s Test? Once your initial ANOVA has found a significant difference in three or more means, Dunn’s Test can be used to pinpoint which specific means are significant from the others. The null hypothesis for the test is that there is no difference between groups (groups can be equal or unequal in size).
How is P adjusted calculated?
Following the Vladimir Cermak suggestion, manually perform the calculation using, adjusted p-value = p-value*(total number of hypotheses tested)/(rank of the p-value), or use R as suggested by Oliver Gutjahr p. adjust(c(X),method=”BH”), here the vector of uncorrected p-values are given by X.
Why are Bonferroni adjusted p-values not reported?
The reason for this is that probabilities cannot exceed 1. With respect to the previous example, this means that if an LSD p-value for one of the contrasts were .500, the Bonferroni-adjusted p-value reported would be 1.000 and not 1.500, which is the product of .5 multiplied by 3
How to perform Dunn’s test with Bonferroni correction?
#load library library (FSA) #perform Dunn’s Test with Bonferroni correction for p-values dunnTest (pain ~ drug, data=data, method=”bonferroni”) Dunn (1964) Kruskal-Wallis multiple comparison p-values adjusted with the Bonferroni method.
What is the p-value of Dunn’s test?
Since the overall p-value (0.003879) is less than .05, this means there is a statistically significant difference between the reported pain levels among the three drugs. Thus, we can perform Dunn’s test to determine exactly which drugs are different.
How are p values adjusted for multiple comparisons?
There are several ways to adjust the p-values, but the two most common adjustment methods are: 1. The Bonferroni Adjustment 2. The Sidak Adjustment By using one of these p-value adjustments, we can dramatically reduce the probability of committing a type I error among the set of multiple comparisons.