Researchers often rely on analysis of variance (ANOVA) when they report results experiments. To ensure that a study is adequately powered to yield informative with an ANOVA, researchers can perform priori power analysis. However, for factorial ANOVA designs challenge. Current software solutions do not allow analyses complex several within-participants factors. Moreover, need [Formula: see text]...

ANOVA is a statistical tool commonly used to study factor effects. Usually a model is selected through hypothesis testing or according to some model selection criteria. Both approaches have difficulties in finding the best model. When the goal is to estimate the cell means rather than to select a model, we proposed an algorithm, ARM, to convexly combine the candidate models. Simulation and data...

In a zebrafish recessive mutant young (yng), retinal cells are specified to distinct cell classes, but they fail to morphologically differentiate. A null mutation in a brahma-related gene 1 (brg1) is responsible for this phenotype. To identify retina-specific Brg1-regulated genes that control cellular differentiation, we conducted a factorial microarray analysis. Gene expression profiles were c...

Inferences we make about underlying cognitive processes can be jeopardized in two ways due to problematic forms of aggregation. First, averaging across individuals is typically considered a very useful tool for removing random variability. The threat is that averaging across subjects leads to averaging across different cognitive strategies, thus harming our inferences. The second threat comes f...