$\begingroup$ In my understanding if the underlying dataset is the same, you should apply Bonferroni correction. Note … Although the Bonferroni correction is very simple, it reduces the power of tests, thus making the testing procedure very conservative. 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 A survey records the level of spending of men and women on 10 categories of consumer goods. For example, for two hypothesis tests, an overall of .05 could be maintained by conducting one test at .04 and the other at .01. The Bonferroni correction was specifically applied in 51 (36%) of articles, other types of correction such as the Bonferroni‐Holm method, standard Abbott formula, the false discovery rate, the Hochberg method, or an alternative conservative post‐hoc procedure, such as … In such cases, the Bonferroni-corrected p-value reported by SPSS will be 1.000. We now correct for multiple hypothesis testing by applying the Bonferroni correction to every row (or column, since the matrix is symmetric) and we're done. $\endgroup$ – Vladislavs Dovgalecs Mar 8 '16 … Bonferroni Test: A type of multiple comparison test used in statistical analysis. Example. For example, if 100 experiments are performed (N = 100), and the required significance level is α = 0.05, the Bonferroni correction requires α B = 0.0005.
The mean level of spending on each category will be compared, ie 10 tests will be carried out.
The reason for this is that probabilities cannot exceed 1. The Bonferroni correction can be …
To achieve an overall significance level of = 0.05, the Bonferroni method requires a … Confidence intervals.
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