This paper is an overview of a unified framework for analyzing designed experiments with univariate or multivariate responses. Both categorical and continuous design variables are considered. To handle unbalanced data, we introduce the so-called Type II* sums of squares. This means that the...

A brief review is given of procedures for the collective analysis of a large number of significance tests. A simple procedure previously supplied for isolating 'real' effects on the basis of a large number of significance tests is generalized to deal with two-sided tests and is also related more...

We outline a method of sample size calculation in microarray experiments on the basis of pilot data and illustrate its practical application with both simulated and real data. The method was shown to be consistent (as the number of `probed genes' tends to infinity) under general conditions in an...

For testing multiple null hypotheses, the classical approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, one might be willing to tolerate more...

In a recent article in PLoS Genetics, Bock et al., (2006) undertake an extensive computational epigenetics analysis of the ability of DNA sequence-derived features, capturing attributes such as tetramer frequencies, repeats and predicted structure, to predict the methylation status of CpG...