IsoGene1: The five test statistics calculated for both the increasing and decreasing trends

Description

The function calculates the values for the five test statistics (the global likelihood test, Williams, Marcus, M, and the modified M) for testing increasing and decreasing alternatives.

Usage

IsoGene1(x, y)

Arguments

indicates the dose levels

is the gene expression for one gene

Value

E2.up: the test statistic of the global likelihood test for testing increasing alternative.
Williams.up: the test statistic of Williams for testing increasing alternative.
Marcus.up: the test statistic of Marcus for testing increasing alternative.
M.up: the M test statistic for testing increasing alternative.
ModM.up: the test statistic of the modified M for testing increasing alternative.
E2.dn: the test statistic of Williams for testing decreasing alternative.
Williams.dn: the test statistic of global likelihood test for testing decreasing alternative.
Marcus.dn: the test statistic of Williams for testing decreasing alternative.
M.dn: the test statistic of global likelihood test for testing decreasing alternative.
ModM.dn: the test statistic of Williams for testing increasing alternative.
direction: the direction with the higher likelihood of increasing (indicated by "u") or decreasing (indicated by "d") trend.

References

Modeling Dose-response Microarray Data in Early Drug Development Experiments Using R, Lin D., Shkedy Z., Yekutieli D., Amaratunga D., and Bijnens, L. (editors), (2012), Springer.

Testing for Trend in Dose-Response Microarray Experiments: a Comparison of Testing Procedures, Multiplicity, and Resampling-Based Inference, Lin et al. 2007, Stat. App. in Gen. & Mol. Bio., 6(1), article 26.

IsoGene: An R Package for Analyzing Dose-response Studies in Microarray Experiments, Pramana S., Lin D., Haldermans P., Shkedy Z., Verbeke T., De Bondt A., Talloen W., Goehlmann H., Bijnens L. 2010, R Journal 2/1.

Examples

Run this code

  x <- c(rep(1,3),rep(2,3),rep(3,3),rep(4,3))
  y <- c(rnorm(3,1,1),rnorm(3,2,1),rnorm(3,3,1),rnorm(3,4,1))
  stat <- IsoGene1(x,y)
  stat