intraAnalysisClassic {BLMA} | R Documentation

## Intra-experiment analysis in conjunction with classical hypothesis tests

### Description

Perform an intra-experiment analysis in conjunction with any of the classical hypothesis testing methods, such as t-test, Wilcoxon test, etc.

### Usage

    intraAnalysisClassic(x, y = NULL, splitSize = 5, metaMethod = addCLT,
      func = t.test, p.value = "p.value", ...)

### Arguments

`x` | a numeric vector of data values
`y` | an optional numeric vector of values
`splitSize` | the minimum number of size in each split sample. splitSize should be at least 3. By default, splitSize=5
`metaMethod` | the method used to combine p-values. This should be one of addCLT (additive method [1]), fishersMethod (Fisher's method [5]), stoufferMethod (Stouffer's method [6]), max (maxP method [7]), or min (minP method [8])
`func` | the name of the hypothesis test. By default func=t.test
`p.value` | the component that returns the p-value after performing the test provided by the func parameter. For example, the function t-test returns the class "htest" where the component "p.value" is the p-value of the test. By default, p.value="p.value"
`...` | additional parameters for func

### Details

This function performs an intra-experiment analysis for the given sample(s) [1]. Given x as the numeric vector, this function first splits x into smaller samples with size splitSize, performs hypothesis testing using func, and then combines the p-values using metaMethod

### Value

intra-experiment p-value

### Author(s)

Tin Nguyen and Sorin Draghici

### References

[1] T. Nguyen, R. Tagett, M. Donato, C. Mitrea, and S. Draghici. A novel bi-level meta-analysis approach – applied to biological pathway analysis. Bioinformatics, 32(3):409-416, 2016.

### See Also

`bilevelAnalysisClassic`, `intraAnalysisGene`, `bilevelAnalysisGene`

### Examples

    set.seed(1)
    x <- rnorm(10, mean = 0)
    # p-value obtained from a one-sample t-test
    t.test(x, mu=1, alternative = "less")$p.value
    # p-value obtained from an intra-experiment analysis
    intraAnalysisClassic(x, func=t.test, mu=1, alternative = "less")

    # p-value obtained from a one-sample wilcoxon test
    wilcox.test(x, mu=1, alternative = "less")$p.value
    # p-value obtained from an intra-experiment analysis
    intraAnalysisClassic(x, func=wilcox.test, mu=1, alternative = "less")

    set.seed(1)
    x <- rnorm(20, mean=0); y <- rnorm(20, mean=1)
    # p-value obtained from a two-sample t-test
    t.test(x,y,alternative="less")$p.value
    # p-value obtained from an intra-experiment analysis
    intraAnalysisClassic(x, y, func=t.test, alternative = "less")
    # p-value obtained from a two-sample wilcoxon test
    wilcox.test(x,y,alternative="less")$p.value
    # p-value obtained from an intra-experiment analysis
    intraAnalysisClassic(x, y, func=wilcox.test, alternative = "less")

[Package BLMA version 1.6.0 Index]