Description Usage Arguments Details Value References See Also Examples
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.
1 | mcpbon(y, ind, alpha = 0.05)
|
y |
Vector of the combined samples of size n |
ind |
Corresponding treatment vector of size n |
alpha |
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
j
& jp
are the specific levels (categories of cars) being compared.
muj
& mujp
are the means of two levels being compared. diff
is the difference in means between these levels. se
is the standard
error for each comparison, err
is the comparison's error estimate, and
lb
& ub
consist of the lower and upper bound for each comparison's
confidence interval.
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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