mutoss (version 0.1-9)

compareMutoss: Functions for comparing outputs of different procedures.

Description

Functions for comparing outputs of different procedures.

Usage

compareMutoss(...)
mu.compare.adjusted(comparison.list, identify.check=F)
mu.compare.critical(comparison.list, identify.check=F)
mu.compare.summary(comparison.list)

Arguments

...

An arbitrary number of Motoss class objects.

comparison.list

The output of the compareMutoss function.

identify.check

Logical parameter specifying if hypotheses should be identified on the output plots.

Value

• compareMutoss
  Returns a list with the following components: types: Character vector of error types corrsponding to each procedure. rates: Numeric vector of error rates used for each procedure. pi.nulls: Numeric vector of estimates of the proportion of true null hypothesis if avilable. raw.pValues: The raw p-values used for each procedure. adjusted.pvals: Data frame with columns holding procedure specific adjusted p values. criticalValue: Data frame with columns holding the critical values corresponding to each procedure and error rate. rejections: Data frame with columns holding logical vectors of rejected hypotheses (TRUE for rejected).
• mu.compare.adjusted
  Creates a plot with the adjusted p-values for each procedure.
• mu.compare.critical
  Creates a plot with the critical values for each procedure and error rate.
• mu.compare.summary
  Creates a short textual summary for comparing results of different procedures.

Details

These functions are used to compare the results of different multiple comparisons procedures stored as Mutoss class objects. compareMutoss takes as input an arbitrary number of Mutoss objects and arranges them in a simple list objects (non S4). mu.compare.adjuted, mu.compare.critical and mu.compare.summary take the output of the compareMutoss and plots or summerize the results textually or graphically.

Examples

# TODO: EXAMPLE PROBLEMS
\dontrun{Creating several Mutoss class objects}
mu.test.obj.1 <- mutoss.apply(new(Class="Mutoss", 
                                  pValues=runif(10)), 
                                  f=bonferroni, 
                                  label="Bonferroni Correction", 
                                  alpha=0.05, 
                                  silent=T)
mu.test.obj.2 <- mutoss.apply(new(Class="Mutoss", 
                                  pValues=runif(10)), 
                                  f=holm, 
                                  label="Holm's step-down-procedure", 
                                  alpha=0.05,
                                  silent=T)
mu.test.obj.3 <- mutoss.apply(new(Class="Mutoss", 
                                  pValues=runif(10)), 
                                  f=aorc, 
                                  label="Asymtotically optimal rejection curve", 
                                  alpha=0.05, 
                                  startIDX_SUD = 1, 
                                  silent=T)
\dontrun{Trying to coercing a non-Mutoss object}
compareMutoss(1)
\dontrun{ Coercing several objects into a list}
compare.1<- compareMutoss(mu.test.obj.1, mu.test.obj.2)
compare.2<- compareMutoss(mu.test.obj.1, mu.test.obj.2, mu.test.obj.3)
\dontrun{Plotting the adjusted pvalues. Identification available.}
mu.compare.adjusted(compare.1, T)
mu.compare.adjusted(compare.2, T)
\dontrun{Plotting the critical values. Identification available.}
mu.compare.critical(compare.1, T)
mu.compare.critical(compare.2, T)
\dontrun{Showing a textual sumary}
mu.compare.summary(compare.1)
mu.compare.summary(compare.2)