A 2×2 Factorial Design for Double Reversal Feeding Experiments

Model-averaged confidence intervals for factorial experiments

We consider the coverage rate of model-averaged confidence intervals for the treatment means in a factorial experiment, whenwe use a normal linearmodel in the analysis.Modelaveraging provides a useful compromise between using the full model (containing all main effects and interactions) and a ‘‘best model’’ obtained by some model-selection process. Use of the full model guarantees perfect cover...

Optimal Factorial Designs for Cdna Microarray Experiments

We consider cDNA microarray experiments when the cell populations have a factorial structure, and investigate the problem of their optimal designing under a baseline parametrization where the objects of interest differ from those under the more common orthogonal parametrization. First, analytical results are given for the 2× 2 factorial. Since practical applications often involve a more complex...

Factorial Design

investigating the feasibility of a proposed model for geometric design of deployable arch structures

deployable scissor type structures are composed of the so-called scissor-like elements (sles), which are connected to each other at an intermediate point through a pivotal connection and allow them to be folded into a compact bundle for storage or transport. several sles are connected to each other in order to form units with regular polygonal plan views. the sides and radii of the polygons are...

A Bootstrap Correspondence Analysis for Factorial Microarray Experiments with Replications

Characterized by simultaneous measurement of the effects of experimental factors and their interactions, the economic and efficient factorial design is well accepted in microarray studies. To date, the only statistical method for analyzing microarray data obtained using factorial design has been the analysis of variance (ANOVA) model which is a gene by gene approach and relies on multiple assum...