Split-Plot Designs: What, Why, and How Jones, Bradley; Nachtsheim, Christopher J.
Journal of quality technology,
10/2009, Volume:
41, Issue:
4
Journal Article
Peer reviewed
The past decade has seen rapid advances in the development of new methods for the design and analysis of split-plot experiments. Unfortunately, the value of these designs for industrial ...experimentation has not been fully appreciated. In this paper, we review recent developments and provide guidelines for the use of split-plot designs in industrial applications.
A number of statistical textbooks recommend using an analysis of covariance (ANCOVA) to control for the effects of extraneous factors that might influence the dependent measure of interest. However, ...it is not generally recognized that serious problems of interpretation can arise when the design contains comparisons of participants sampled from different populations (classification designs). Designs that include a comparison of younger and older adults, or a comparison of musicians and non-musicians are examples of classification designs. In such cases, estimates of differences among groups can be contaminated by differences in the covariate population means across groups. A second problem of interpretation will arise if the experimenter fails to center the covariate measures (subtracting the mean covariate score from each covariate score) whenever the design contains within-subject factors. Unless the covariate measures on the participants are centered, estimates of within-subject factors are distorted, and significant increases in Type I error rates, and/or losses in power can occur when evaluating the effects of within-subject factors. This paper: (1) alerts potential users of ANCOVA of the need to center the covariate measures when the design contains within-subject factors, and (2) indicates how they can avoid biases when one cannot assume that the expected value of the covariate measure is the same for all of the groups in a classification design.
Qualitative Data Auerbach, Carl; Silverstein, Louise B
2003, Volume:
21
eBook
Qualitative Data is meant for the novice researcher who needs guidance on what specifically to do when faced with a sea of information. It takes readers through the qualitative research process, ...beginning with an examination of the basic philosophy of qualitative research, and ending with planning and carrying out a qualitative research study. It provides an explicit, step-by-step procedure that will take the researcher from the raw text of interview data through data analysis and theory construction to the creation of a publishable work.
The volume provides actual examples based on the authors' own work, including two published pieces in the appendix, so that readers can follow examples for each step of the process, from the project's inception to its finished product. The volume also includes an appendix explaining how to implement these data analysis procedures using NVIVO, a qualitative data analysis program.
The benefits of sequential design of experiments have long been described for both model‐based and space‐filling designs. However, in our experience, too few practitioners take advantage of the ...opportunity afforded by this approach to maximize the learning from their experimentation. By obtaining data sequentially, it is possible to learn from the early stages to inform subsequent data collection, minimize wasted resources, and provide answers for a series of objectives for the overall experiment. This paper provides methods and algorithms to create augmented distance‐based space‐filling designs, using both uniform and non‐uniform space‐filling strategies, that can be constructed at each stage based on information learned in earlier stages. We illustrate the methods with several examples that involve different initial data, types of space‐filing designs and experimental goals.
According to Quality by Design (QbD) concept, quality should be built into product/method during pharmaceutical/analytical development. Usually, there are many input factors that may affect quality ...of product and methods. Recently, Design of Experiments (DoE) have been widely used to understand the effects of multidimensional and interactions of input factors on the output responses of pharmaceutical products and analytical methods. This paper provides theoretical and practical considerations for implementation of Design of Experiments (DoE) in pharmaceutical and/or analytical Quality by Design (QbD). This review illustrates the principles and applications of the most common screening designs, such as two-level full factorial, fractionate factorial, and Plackett-Burman designs; and optimization designs, such as three-level full factorial, central composite designs (CCD), and Box-Behnken designs. In addition, the main aspects related to multiple regression model adjustment were discussed, including the analysis of variance (ANOVA), regression significance, residuals analysis, determination coefficients (R2, R2-adj, and R2-pred), and lack-of-fit of regression model. Therefore, DoE was presented in detail since it is the main component of pharmaceutical and analytical QbD.
Children's Spaces Dudek, Mark
2005, 20120504, 2005-06-01, 2012-05-04
eBook
This collection of essays is concerned with the experiences children have within the supervised worlds they inhabit, as well as with architecture and landscape architecture.International examples of ...innovative childcare practice are illustrated together with the design processes which informed their development. The emphasis here is on new and experimental childcare projects which set-out to reassert the rights of children to participate in a complex multi-faceted world, which is no longer available to them, unless under adult supervision. Research supports in depth recommendations regarding the ideal children's environment, across a range of contexts and dimensions. Until recent times, the needs of children within the urban environment were largely ignored. There is little tradition and no broadly agreed contemporary architectural or landscape theory as to how children should be provided for, beyond a limited functional agenda. There is a sense that architecture for childhood is not taken seriously; it is either whimsical and ephemeral or largely designed for adults, an adjunct to the more important business of adult needs and aspirations. Yet children access much of their education and development through play and social interaction with their childhood counterparts. The spaces in and around children"s daycare centres, schools, supervised parks and other dedicated children"s environments are the subject of this collection. As more and more purpose designed buildings and gardens for children are opened, the need to listen to children and their carers is becoming more aparant. Mark Dudek gathers together a number of internationally recognized experts in the field of childcare environments to write about different aspects of the landscape. They have been chosen in particular because of their background in enquiring, research orie
Longitudinal panel studies are widely used in developmental science to address important research questions on human development across the lifespan. These studies, however, are often challenging to ...implement. They can be costly, time‐consuming, and vulnerable to test–retest effects or high attrition over time. Planned missingness designs (PMDs), in which partial data are intentionally collected from all or some of the participants, are viable solutions to these challenges. This article provides an overview of several PMDs with potential utilities in longitudinal studies, including the multi‐form designs, multi‐method designs, varying lag designs, accelerated longitudinal designs, and efficient designs for analysis of change. For each of the designs, the basic rationale, design considerations, data analysis, advantages, and limitations are discussed. The article is concluded with some general recommendations to developmental researchers and promising directions for future research.
Modelling is a central activity in practical engineering and something that is also useful in engineering education research (EER). Additionally, qualitative research methods have found important ...applications in engineering research, although their use in EER has not always been widely accepted. Design science research is a qualitative research approach in which the object of study is the design process, i.e. it simultaneously generates knowledge about the method used to design an artefact and the design or the artefact itself. This paper uses techniques from design science research to analyse the method used when deriving the 'learning of a complex concept' (LCC) model, which we developed while designing teaching sequences for a course on electrical engineering. Our results demonstrate the value of design science research in EER and suggest that the LCC model is generally applicable in this field.
Let X be a finite set with v elements, called points and β be a family of subsets of X, called blocks. A pair (X,β) is called λ‐design whenever ∣β∣=∣X∣ and
1.
for all Bi,Bj∈β,i≠j,∣Bi∩Bj∣=λ;
2.
for ...all Bj∈β,∣Bj∣=kj>λ, and not all kj are equal. The only known examples of λ‐designs are so‐called type‐1 designs, which are obtained from symmetric designs by a certain complementation procedure. Ryser and Woodall had independently conjectured that all λ‐designs are type‐1. Let r,r*(r>r*) be replication numbers of a λ‐design D=(X,β) and g=gcd(r−1,r*−1),m=gcd((r−r*)∕g,λ), and m′=m, if m is odd and m′=m∕2, otherwise. For distinct points x and y of D, let λ(x,y) denote the number of blocks of X containing x and y. We strengthen a lemma of S.S. Shrikhande and N.M. Singhi and use it to prove that if r(r−1)(v−1)−k(r−r*)m′(v−1) are not integers for k=1,2,…,m′−1, then D is type‐1. As an application of these results, we show that for fixed positive integer θ there are finitely many nontype‐1 λ‐designs with r=r*+θ. If r−r*=27 or r−r*=4p and r*≠(p−1)2, or v=7p+1 such that p≢1,13(mod21) and p≢4,9,19,24(mod35), where p is a positive prime, then D is type‐1. We further obtain several inequalities involving λ(x,y), where equality holds if and only if D is type‐1.
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