Using Individual Factor Information in Fractional Factorial Designs

<p>While literature on constructing efficient experimental designs has been plentiful, how best to incorporate prior information when assigning factors to the columns of a nonregular design has received little attention. Following Li, Zhou, and Zhang (<a href="#cit0009" target="_blank">2015</a>), we propose the individual generalized word length pattern (iGWLP) for ranking columns of a nonregular design. Taking examples from the literature of recommended orthogonal arrays, we illustrate how iGWLP helps to identify important differences in the aliasing that is likely otherwise missed. Given the complexity of characterizing partial aliasing for nonregular designs, iGWLP will help practitioners make more informed assignment of factors to columns when using nonregular fractions. We provide theoretical justification of the proposed iGWLP. A theorem is given to relate the proposed iGWLP criterion to the expected bias caused by model misspecifications. We also show that the proposed criterion may lead to designs having better projection properties in the factors considered most likely to be important. Furthermore, we discuss how iGWLP can be used for design selection. We propose a criterion for choosing best designs when the focus is on a small set of important factors, for which the aliasing of effects involving these factors is minimized.</p

A Systematic View of Information-Based Optimal Subdata Selection: Algorithm Development, Performance Evaluation, and Application in Financial Data

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Benefits and Fast Construction of Efficient Two-Level Foldover Designs

<p>Recent work in two-level screening experiments has demonstrated the advantages of using small foldover designs, even when such designs are not orthogonal for the estimation of main effects (MEs). In this article, we provide further support for this argument and develop a fast algorithm for constructing efficient two-level foldover (EFD) designs. We show that these designs have equal or greater efficiency for estimating the ME model versus competitive designs in the literature and that our algorithmic approach allows the fast construction of designs with many more factors and/or runs. Our compromise algorithm allows the practitioner to choose among many designs making a trade-off between efficiency of the main effect estimates and correlation of the two-factor interactions (2FIs). Using our compromise approach, practitioners can decide just how much efficiency they are willing to sacrifice to avoid confounded 2FIs as well as lowering an omnibus measure of correlation among the 2FIs.</p

Additional file 1: of Development of a community-based network to promote smoking cessation among female smokers in Hong Kong

The file is a copy of the questionnaire used in this study. The questionnaire was used to identify the learning needs of WATT members in Phase I. It measured the (1) knowledge, (2) attitudes, and (3) practice of tobacco control and smoking cessation. The WATT members who took part in Phase II were also asked to complete this questionnaire before, immediately after and 6 months after the training workshop. (DOC 168 kb

Additional file 1: of Motivating smokers at outdoor public smoking hotspots to have a quit attempt with a nicotine replacement therapy sample: study protocol for a randomized controlled trial

SPIRIT checklist for standard protocol items. (DOC 117 kb