mt.teststat {multtest} | R Documentation

## Computing test statistics for each row of a data frame

### Description

These functions provide a convenient way to compute test statistics, e.g., two-sample Welch t-statistics, Wilcoxon statistics, F-statistics, paired t-statistics, block F-statistics, for each row of a data frame.

### Usage

    mt.teststat(X,classlabel,test="t",na=.mt.naNUM,nonpara="n")
    mt.teststat.num.denum(X,classlabel,test="t",na=.mt.naNUM,nonpara="n")

### Arguments

`X` | A data frame or matrix, with m rows corresponding to variables (hypotheses) andn columns to observations. In the case of gene expression data, rows correspond to genes and columns to mRNA samples. The data can be read using `read.table`.
`classlabel` | A vector of integers corresponding to observation (column) class labels. For k classes, the labels must be integers between 0 and k-1. For the `blockf` test option, observations may be divided into n/k blocks of k observations each. The observations are ordered by block, and within each block, they are labeled using the integers 0 to k-1.

`test`

A character string specifying the statistic to be used to test the null hypothesis of no association between the variables and the class labels.
If `test="t"`, the tests are based on two-sample Welch t-statistics (unequal variances).
If `test="t.equalvar"`, the tests are based on two-sample t-statistics with equal variance for the two samples. The square of the t-statistic is equal to an F-statistic for k=2.
If `test="wilcoxon"`, the tests are based on standardized rank sum Wilcoxon statistics.
If `test="f"`, the tests are based on F-statistics.
If `test="pairt"`, the tests are based on paired t-statistics. The square of the paired t-statistic is equal to a block F-statistic for k=2.
If `test="blockf"`, the tests are based on F-statistics which adjust for block differences (cf. two-way analysis of variance).

`na` | Code for missing values (the default is `.mt.naNUM=--93074815.62`). Entries with missing values will be ignored in the computation, i.e., test statistics will be based on a smaller sample size. This feature has not yet fully implemented.
`nonpara` | If `nonpara`="y", nonparametric test statistics are computed based on ranked data. If `nonpara`="n", the original data are used.

### Value

For `mt.teststat`, a vector of test statistics for each row (gene).
For `mt.teststat.num.denum`, a data frame with

`teststat.num` | the numerator of the test statistics for each row, depending on the specific `test` option.
`teststat.denum` | the denominator of the test statistics for each row, depending on the specific `test` option.

### Author(s)

Yongchao Ge, yongchao.ge@mssm.edu,
Sandrine Dudoit, http://www.stat.berkeley.edu/~sandrine.

### See Also

`mt.maxT`, `mt.minP`, `golub`.

### Examples

    # Gene expression data from Golub et al. (1999)
    data(golub)

    teststat<-mt.teststat(golub,golub.cl)
    qqnorm(teststat)
    qqline(teststat)

    tmp<-mt.teststat.num.denum(golub,golub.cl,test="t")
    num<-tmp$teststat.num
    denum<-tmp$teststat.denum
    plot(sqrt(denum),num)

    tmp<-mt.teststat.num.denum(golub,golub.cl,test="f")

[Package multtest version 2.0.0 Index]