Interpreting 'omics data often involves statistical analysis of large numbers of loci such as genes, binding sites or single-nucleotide polymorphisms (SNPs). Although the data set as a whole may be ...

The availability of large volumes of data is a key requirement in the development of efficient, robust, and advanced machine learning based prediction models. This paper introduces the ImageNet ...

This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this ...

Hierarchical data analyses in different disciplines are reviewed to compare statistical applications of the Hierarchical Linear Model (HLM) software and the SAS MIXED procedure. Similar features of ...