mcpbon: Bonferroni's Multiple Comparisons Procedure

Description Usage Arguments Details Value References See Also Examples

Description

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.

Usage

1
mcpbon(y, ind, alpha = 0.05)

Arguments

y

Vector of the combined samples of size n

ind

Corresponding treatment vector of size n

alpha

Level of significance used for Bonferroni Procedure

Details

Computes the Bonferroni confidence intervals as seen in Example 9.4.1 on page 529.

Value

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.

References

Hogg, R., McKean, J., Craig, A. (2018) Introduction to Mathematical Statistics, 8th Ed. Boston: Pearson.

See Also

mcpfisher() for details about Fisher's PLSD Multiple Comparison Procedure

Examples

1
2
3
speed <- fastcars$speed
car <- fastcars$ind
mcpbon(speed, car)

joemckean/mathstat documentation built on May 30, 2019, 2:01 p.m.