mdd.mantelhaen {MDD}R Documentation

MDD for Cochran-Mantel-Haenszel Test

Description

For a specified number of control responses in each stratum, calculate all possible treatment response scenarios for which the Cochran-Mantel-Hanszel test will be significant, and optionally (by default) print out a paragraph summarizing the results.

Usage

mdd.mantelhaen(placebo.size, treat.size, placebo.vals, alpha = 0.05, 
               alternative = "two.sided", exact = TRUE, print.summary = TRUE)

Arguments

placebo.size a vector with the number of subjects in each stratum assigned to the control group.
treat.size a vector with the number of subjects in each stratum assigned to the treatment group.
placebo.vals a vector with the number of responses to be observed in each control stratum.
alpha significance level.
alternative indicates the alternative hypothesis and must be one of "two.sided", "greater", or "less". You can specify just the initial letter.
exact a logical value indicating whether to do an exact conditional test or use the C-M-H test statistic.
print.summary a logical value indicating whether to print a paragraph summarizing the calculations.

Value

A list with the following two components:

le A matrix with rows consisting of all non-comparable (see below) treatment response scenarios for which the test statistic will be significant by virtue of the treatment response rate being less than the control response rate.
gr A matrix with rows consisting of all non-comparable (see below) treatment response scenarios for which the test statistic will be significant by virtue of the treatment response rate being greater than the control response rate.

If print.summary = TRUE, then this is returned invisibly.

Warning

Run times for this program can be extremely long for data sets with either a large number of strata or a large number of subjects.

The Warning section of mdd.mantelhaen.pow explains a problem with the algorithm used in that program which might or might not also show up for this program. (It's virtually certain that it can, but I have not constructed an example to verify this.)

Note

“Non-comparable” refers to the fact that if, for example, c(2,3) is in the le component, then c(2,2), c(1,3), c(1,2), etc., would all be significant as well. On the other hand, c(3,2) and c(0,4) might or might not be. In particular, for any two rows in the le component, there will be at least one column which is strictly greater in the first row than the second, and at least one column which is strictly greater in the second row than the first; and similarly for the gr component.

For one-sided tests, at least one of the two components of the return value will automatically be empty.

This function does the same job as mdd.mantelhaen.pow(..., to.file="file.Rdata") followed by extract.mdd.mantelhaen(..., from.file="file.RData"), but much more quickly.

Author(s)

Don Barkauskas (barkda@wald.ucdavis.edu)

References

See mantelhaen.test for references.

See Also

extract.mdd.mantelhaen, mdd.mantelhaen.pow

gui.mdd for a GUI version

Examples

mh.ex <- mdd.mantelhaen(c(11,10,10), c(11,10,10), c(4,3,3))

#For a two-sided test at significance level 0.05, with 31 control subjects 
#(split 11, 10, and 10 among the strata) and 31 treatment subjects (split 11, 
#10, and 10 among the strata), and 10 observed control responses (split 4, 3, 
#and 3 among the strata).
#
#With 19 or more, or 2 or fewer, treatment responses, the test will be 
#significant no matter how the responses are distributed across the strata.  
#With exactly 18 treatment responses, whether or not the test is significant 
#depends on how the responses are distributed across the strata.

head(mh.ex$gr)

#The first row tells us, for example, that c(0,9,10), c(0,10,10), and c(1,9,10)
#would all be significant.

head(mh.ex$le)

#The second row tells us, for example, that c(0,1,1), c(0,0,1), and c(0,1,0)
#would all be significant.

rm(mh.ex)

[Package MDD version 0.5 Index]