Description Usage Arguments Details Value References See Also Examples
The mdir.logrank function calculates the multipledirection logrank statistic and its corresponding pvalues based on a χ^2approximation and a permutation approach
1 2  mdir.logrank(data, cross = TRUE, rg = list(c(0, 0)), nperm = 10000,
dig_p = 3, dig_stat = 3)

data 
A data.frame, list or environment containing the variables 
cross 
logical. Should the weight corresponding to crossing hazards be included?
The default is 
rg 
A list (or 
nperm 
The number of permutations used for calculating the permuted pvalue. The default option is 10000. 
dig_p 
The pvalues are rounded to 
dig_stat 
The test statistic is rounded to 
The package provides the multipledirection logrank statistic for
the two sample testing problem within rightcensored survival data. Directions
of the form w(x) = 1  2x (cross = TRUE
) and w(x) = x^r * (1x)^g for natural numbers
r,g (including 0) can be specified.
The multipledirection logrank test needs linearly independent directions.
A check for this is implemented. If the directions chosen by the user are
linearly dependent then a subset consisting of linearly independent directions
is selected automatically.
The mdir.logrank
function returns the test statistic as well as two
corresponding pvalues: the first is based on a chi^2 approximation and
the second one is based on a permutation procedure.
An mdirLR
object containing the following components:
Descriptive 
The directions used and whether the directions specified by the user were linearly independent. 
p.values 
The pvalues of the multipledirection logrank test using the χ^2approximation (Approx.) as well as the one using the permutation approach (Perm.). 
stat 
Value of the multipledirection logrank statistic. 
rg 
A list containing the exponents of the direction considered in the statistical analysis. 
cross 
logical. Was the crossing direction considered in the statistical analysis? 
indep 
logical. Were the directions specified by the user linearly independent? 
nperm 
The number of permutations used for calculating the permuted pvalue. 
Ditzhaus, M., Friedrich, S. (2018). More powerful logrank permutation tests for twosample survival data. arXiv preprint arXiv:1807.05504.
mdir.onesided
(onesided test)
1 2 3 4 5 6  library(coin)
data(GTSG)
out < mdir.logrank(data = GTSG, nperm = 1000)
## Detailed information:
summary(out)

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