Phantom Classrooms

McLean, Leslie D.

doi:10.1086/442766

Cited by 5 publications

(3 citation statements)

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“…Allore, Peduzzi, Han, & Tinetti, 2006; Allore, Tinettia, Gill, & Peduzzi, 2005), marketing research (e.g. Holland & Cravens, 1973), epidemiology (Taylor et al, 1994), education (McLean, 1966), human factors (Simon & Roscoe, 1984), and legal psychology (Stolle, Robbennolt, Patry, & Penrod, 2002). Shaw (2004) and Shaw, Festing, Peers, & Furlong (2002) noted that factorial and fractional factorial designs can help to reduce the number of animals that must be used in laboratory research.…”

Section: Discussionmentioning

confidence: 99%

“…One of the objectives of this article was to demonstrate that fractional factorial designs merit consideration for use in psychological research alongside other reduced designs and complete factorial designs. Previous authors have noted that fractional factorial designs may be useful in a variety of areas within the social and behavioral sciences (Landsheer & van den Wittenboer, 2000), such as behavioral medicine (e.g., Allore, Peduzzi, Han, & Tinetti, 2006; Allore, Tinetti, Gill, & Peduzzi, 2005), marketing research (e.g., Holland & Cravens, 1973), epidemiology (Taylor et al, 1994), education (McLean, 1966), human factors (Simon & Roscoe, 1984), and legal psychology (Stolle, Robbennolt, Patry, & Penrod, 2002). Shaw (2004) and Shaw, Festing, Peers, and Furlong (2002) noted that factorial and fractional factorial designs can help reduce the number of animals that must be used in laboratory research.…”

Section: Discussionmentioning

confidence: 99%

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Design of experiments with multiple independent variables: A resource management perspective on complete and reduced factorial designs.

Collins¹,

Dziak²,

Li³

2009

Psychological Methods

352

284

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An investigator who plans to conduct experiments with multiple independent variables must decide whether to use a complete or reduced factorial design. This article advocates a resource management perspective on making this decision, in which the investigator seeks a strategic balance between service to scientific objectives and economy. Considerations in making design decisions include whether research questions are framed as main effects or simple effects; whether and which effects are aliased (confounded) in a particular design; the number of experimental conditions that must be implemented in a particular design and the number of experimental subjects the design requires to maintain the desired level of statistical power; and the costs associated with implementing experimental conditions and obtaining experimental subjects. In this article four design options are compared: complete factorial, individual experiments, single factor, and fractional factorial designs. Complete and fractional factorial designs and single factor designs are generally more economical than conducting individual experiments on each factor. Although relatively unfamiliar to behavioral scientists, fractional factorial designs merit serious consideration because of their economy and versatility.Keywords experimental design; fractional factorial designs; factorial designs; reduced designs; resource management Suppose a scientist is interested in investigating the effects of k independent variables, where k > 1. For example, Bolger and Amarel (2007) investigated the hypothesis that the effect of peer social support on performance stress can be positive or negative, depending on whether the way the peer social support is given enhances or degrades self-efficacy. Their experiment could be characterized as involving four factors: support offered (yes or no), nature of support (visible or indirect), message from a confederate that recipient of support is unable to handle Correspondence may be sent to Linda M. Collins, The Methodology Center, Penn State, 204 E. Calder Way, Suite 400, State College, PA 16801; LMCollins@psu.edu. NIH Public Access Author ManuscriptPsychol Methods. Author manuscript; available in PMC 2010 September 1. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript the task alone (yes or no), and message that a confederate would be unable to handle the task (yes or no).One design possibility when k > 1 independent variables are to be examined is a factorial experiment. In factorial research designs, experimental conditions are formed by systematically varying the levels of two or more independent variables, or factors. For example, in the classic two × two factorial design there are two factors each with two levels. The two factors are crossed, that is, all combinations of levels of the two factors are formed, to create a design with four experimental conditions. More generally, factorial designs can include k ≥ 2 factors and can incorporate two or more levels per factor. With four two-level var...

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Design of experiments with multiple independent variables: A resource management perspective on complete and reduced factorial designs.

Collins¹,

Dziak²,

Li³

2009

Psychological Methods

352

284

View full text Add to dashboard Cite

show abstract

“…The three vectors in X c would typically correspond with two main effects or factors of a twoway design in which both factors have two levels, as well as the interaction of these factors; note that the third contrast vector is the element-wise product of the first two columns in X c . It is also interesting to note that X c could be a design matrix for a fractional factorial such as a 2 3 " 1 or a 2 4-2 (Box & Hunter, 1961;McLean, 1966;Mendenhall, 1968). In fact X c would also be appropriate for a 2 2 latin square design, latin squares being special cases of fractional factorials.…”

Section: /: Basic Framework For the Reviewmentioning

confidence: 99%