Bonferroni's approach to Multiple Comparisons Procedure that uses the method of complements, DeMorgan's Laws and Boole's inequality. This procedure is robust and can be used in many settings rather than just one-way design.
mcpbon(y, ind, alpha = 0.05)
Vector of the combined samples of size n
Corresponding treatment vector of size n
Level of significance used for Bonferroni Procedure
Computes the Bonferroni confidence intervals as seen in Example 9.4.1 on page 529.
This function returns a table to the user. The first two columns
jp are the specific levels (categories of cars) being compared.
mujp are the means of two levels being compared.
is the difference in means between these levels.
se is the standard
error for each comparison,
err is the comparison's error estimate, and
ub consist of the lower and upper bound for each comparison's
Hogg, R., McKean, J., Craig, A. (2018) Introduction to Mathematical Statistics, 8th Ed. Boston: Pearson.
mcpfisher() for details about Fisher's PLSD Multiple Comparison Procedure
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