R: Computation of Scores

cscores {exactRankTests} | R Documentation

## Computation of Scores

### Description

This function can be used to compute several scores for a data vector.

### Usage

    ## Default S3 method:
    cscores(y, type=c("Data", "Wilcoxon", "NormalQuantile",
            "AnsariBradley", "Median", "Savage", "ConSal"), int=FALSE,
            maxs=length(y), ... )
    ## S3 method for class 'factor'
    cscores(y, ...)
    ## S3 method for class 'Surv'
    cscores(y, type="LogRank", int=FALSE, maxs=nrow(y), ...)

### Arguments

`y` | a numeric, factor or logical vector or an object of class `Surv`.
`type` | a character string which specifies the type of the scores to be computed. `Data` just returns `y` if `y` is numeric.
`int` | a logical, forcing integer valued scores.
`maxs` | an integer defining the maximal value of the scores if `int=TRUE`.
`...` | additional arguments, not passed to anything at the moment.

### Details

This function will serve as the basis for a more general framework of rank and permutation tests in future versions of this package. Currently, it is only used in the examples.

The logrank scores are computed as given in Hothorn & Lausen (2002).

If integer valued scores are requested (`int = TRUE`), the `scores` are mapped into integers by `round(scores*length(scores)/max(scores))`. See `dperm` for more details.

`type` is self descriptive, except for `ConSal` which implements scores suggested by Conover & Salsburg (1988).

### Value

A vector of scores for `y` with an attribute `scores` indicating the kind of scores used is returned.

### Author(s)

Torsten Hothorn <Torsten.Hothorn@rzmail.uni-erlangen.de>

### References

Torsten Hothorn & Berthold Lausen (2003), On the exact distribution of maximally selected rank statistics. Computational Statistics \& Data Analysis, 43(2), 121-137.

William J. Conover & David S. Salsburg (1988), Locally most powerful tests for detecting treatment effects when only a subset of patients can be expected to "respond" to treatment. Biometrics, 44, 189-196.

### Examples

    y <- rnorm(50)
    # v.d. Waerden scores
    nq <- cscores(y, type="Normal", int=TRUE)
    # quantile for m=20 observations in the first group
    qperm(0.1, nq, 20)

[Package exactRankTests version 0.8-29 Index]