Fisher's PLSD Multiple Comparison Procedure is a two-stage procedure. For a specified level of significance (alpha), the first step consists of the F-test of the hypotheses of equal means. If the test is rejected at level alpha, then the second stage will compute pairwise (1-alpha)100% confidence intervals.
mcpfisher(y, ind, alpha = 0.05)
Vector of the combined samples
Corresponding treatment vector
Level of significance used for Fisher's Procedure
An example of this Fisher's PLSD Multiple Comparison Procedure can be found in Example 9.4.1 on page 529 of HMC (2018).
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.
mcpbon() for details Bonferroni procedure for all pairwise comparisons
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