Factorial Experiments

Collins, Linda M.; Dziak, John J.; Kugler, Kari C.; Trail, Jessica B.

doi:10.1016/j.amepre.2014.06.021

Cited by 335Optimal Experimental Design MethodsStatistical Methods in Clinical TrialsAdvanced Causal Inference Techniques

Factorial Experiments

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Collins, Linda M., Dziak, John J., Kugler, Kari C., Trail, Jessica B.·2014·American Journal of Preventive Medicine

DOI 10.1016/j.amepre.2014.06.021PMC PMC4171184

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Abstract

Background An understanding of the individual and combined effects of a set of intervention components is important for moving the science of preventive medicine interventions forward. This understanding can often be achieved in an efficient and economical way via a factorial experiment, in which two or more independent variables are manipulated. The factorial experiment is a complement to the RCT; the two designs address different research questions.Purpose To offer an introduction to factorial experiments aimed at investigators trained primarily in the RCT.Methods The factorial experiment is compared and contrasted with other experimental designs used commonly in intervention science to highlight where each is most efficient and appropriate.Results Several points are made: factorial experiments make very efficient use of experimental subjects when the data are properly analyzed; a factorial experiment can have excellent statistical power even if it has relatively few subjects per experimental condition; and when conducting research to select components for inclusion in a multicomponent intervention, interactions should be studied rather than avoided.Conclusions Investigators in preventive medicine and related areas should begin considering factorial experiments alongside other approaches. Experimental designs should be chosen from a resource management perspective, which states that the best experimental design is the one that provides the greatest scientific benefit without exceeding available resources.

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Randomised controlled trials were originally developed to test single-component interventions, but psychological interventions usually consist of multiple treatment components.
“Indeed, RCTs were originally developed to test single-component interventions (eg, drugs), but psychological interventions usually consist of multiple treatment components (eg, mindfulness, psychoeducation and action plans).59”
From Optimising psychological treatment for pain after breast cancer: a factorial design study protocol in Denmark (2023) · cites this paper as [59]
The Abstract (Background and Conclusions; page unavailable) discusses multicomponent interventions and describes treatment-package RCTs as comparing a package of components with a control. The paper does not say that RCTs were originally developed to test single-component interventions, nor does it establish that psychological interventions usually have multiple components or give the cited examples. (LLM, conf=0.84)
Experimental — accuracy not yet measured
The Multiphase Optimization Strategy is a methodological framework designed specifically for optimisation of multicomponent interventions.
“The Multiphase Optimization Strategy (MOST) is a methodological framework, conceptually rooted in engineering, designed specifically for optimisation of multicomponent interventions.”
From Optimising psychological treatment for pain after breast cancer: a factorial design study protocol in Denmark (2023) · cites this paper as [59]
The References section identifies MOST as the “multiphase optimization strategy,” and the Advantages of factorial experiments section discusses choosing components for an optimal multicomponent intervention. The paper does not itself describe MOST as a methodological framework designed specifically for that purpose; its substantive discussion is about factorial experiments. (LLM, conf=0.72)
Experimental — accuracy not yet measured
The Multiphase Optimization Strategy enables the systematic identification of active treatment components in multicomponent interventions, including how the presence or absence of one or more components affects the performance of other components.
“Specifically, MOST enables the systematic identification of active treatment components in multicomponent interventions, including how the presence or absence of one or more components affects the performance of other components.59–61”
From Optimising psychological treatment for pain after breast cancer: a factorial design study protocol in Denmark (2023) · cites this paper as [59]
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Experimental — accuracy not yet measured
System identification approaches obtain dynamic systems models that are the basis for designing control systems achieving optimisation.
“System identification approaches are used in engineering to obtain dynamic systems models; these in turn are the basis for the design of control systems which achieve optimization. 45”
From Evaluating Digital Health Interventions (2016) · cites this paper as [45]
MOST's preparatory and optimization phases are more efficient for intervention development than a traditional randomized controlled trial (RCT) because a traditional RCT would take substantially greater resources (time and sample size per RCT) to meet this goal.
“MOST’s preparatory and optimization phases are more efficient for intervention development than a traditional randomized controlled trial (RCT) since it would take substantially greater resources (time and sample size per RCT) to meet this goal [37].”
From Gamified optimized diabetes management with artificial intelligence-powered rural telehealth intervention (GODART): protocol for an optimization pilot and feasibility trial (2025) · cites this paper as [37]

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Statistical Methods for Research Workers
Fisher, R. A. (1945) · American Journal of Clinical Pathology · doi:10.1093/ajcp/15.11.552b · Cited by 10,883 · see citing works
Response Surface Methodology: Process and Product Optimization Using Designed Experiments
Gunst, R. F., Myers, R. H., & Montgomery, D. C. (1996) · Technometrics · doi:10.2307/1270613 · Cited by 9,576 · see citing works
Experimental Design: Procedures for the Behavioral Sciences
Kirk, R. (2013) · doi:10.4135/9781483384733 · Cited by 8,539 · see citing works
Response Surface Methodology: Process and Product Optimization Using Designed Experiments
Gunst, R. F. (1996) · Technometrics · doi:10.1080/00401706.1996.10484509 · Cited by 3,302 · see citing works
Statistical Methods for Research Workers.
I., L., & Fisher, R. A. (1926) · Journal Of The Royal Statistical Society · doi:10.2307/2341488 · Cited by 2,171 · see citing works
A Factorial Trial of Six Interventions for the Prevention of Postoperative Nausea and Vomiting
Apfel, C. C., Korttila, K. T., Abdalla, M., Kerger, H., Turan, A., Vedder, I., Zernak, C., Danner, K., Jokela, R. M., Pocock, S., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa032196 · Cited by 1,550 · see citing works
Design and Analysis of Experiments
Ryan, T. P. (2007) · doi:10.1002/9780470187548.ch12 · Cited by 1,436 · see citing works
Experiments - Planning, Analysis and Parameter Design Optimization
(2001) · Journal of Tropical Pediatrics · doi:10.1093/tropej/47.2.126 · Cited by 1,132 · see citing works
The Multiphase Optimization Strategy (MOST) and the Sequential Multiple Assignment Randomized Trial (SMART)
Collins, L. M., Murphy, S. A., & Strecher, V. (2007) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2007.01.022 · Cited by 1,082 · see citing works
Self-citation
Design of Experiments: Statistical Principles of Research Design and Analysis
Kuehl, R. O. (1999) · Cited by 908 · see citing works
Design of Experiments: Statistical Principles of Research Design and Analysis
Anderson, M. J., & Whitcomb, P. J. (2001) · Technometrics · doi:10.1198/tech.2001.s589 · Cited by 657 · see citing works
A strategy for optimizing and evaluating behavioral interventions
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LeBlanc, E. S., O’Connor, E., Whitlock, E. P., Patnode, C. D., & Kapka, T. J. (2011) · Annals of Internal Medicine · doi:10.7326/0003-4819-155-7-201110040-00006 · Cited by 401 · see citing works
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McClure, J. B., Derry, H., Riggs, K. R., Westbrook, E. W., St. John, J., Shortreed, S. M., Bogart, A., & An, L. C. (2012) · Contemporary Clinical Trials · doi:10.1016/j.cct.2012.06.009 · Cited by 33 · see citing works
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Wolbers, M., Heemskerk, D., Chau, T. T. H., Yen, N. T. B., Caws, M., Farrar, J., & Day, J. (2011) · Trials · doi:10.1186/1745-6215-12-26 · Cited by 25 · see citing works
Using a Fractional Factorial Design to Increase Direct Mail Response atMother JonesMagazine
Ledolter, J., & Swersey, A. J. (2006) · Quality Engineering · doi:10.1080/08982110600846622 · Cited by 16 · see citing works
Selection in factorial experiments with interaction, especially the 2×2 case
Taneja, B. K., & Dudewicz, E. J. (1987) · Acta Mathematica Sinica English Series · doi:10.1007/bf02560033 · Cited by 4 · see citing works

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Lipschitz, J. M., Pike, C. K., Hogan, T. P., Murphy, S. A., & Burdick, K. E. (2023) · Current Treatment Options in Psychiatry · doi:10.1007/s40501-023-00297-3 · Cited by 230 · see citing works
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Authors: Collins, L. M., Dziak, J. J., Kugler, K. C., & Trail, J. B.
Affiliations: Pennsylvania State University (US)
Corresponding author: Collins, Linda M.
ORCID: Collins, Linda M.
Dziak, John J.
Kugler, Kari C.
Venue: American Journal of Preventive Medicine
Publisher: Elsevier BV
Published: 2014-10
Volume: 47
Issue: 4
Pages: 498-504
ISSN: 0749-3797 (ISSN-L)
DOI: 10.1016/j.amepre.2014.06.021
PMC: PMC4171184
OpenAlex: W106021680
Cited by: 335
References: 27
Citations by year: 2026: 29 · 2025: 24 · 2024: 33 · 2023: 35 · 2022: 27 · 2021: 36 · 2020: 53 · 2019: 31 · 2018: 26 · 2017: 21 · 2016: 10 · 2015: 10
FWCI: 17.17
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: American Journal of Preventive Medicine (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institute on Drug Abuse (P50DA010075)
National Cancer Institute (P50CA143188)
National Center for Advancing Translational Sciences (KL2TR000126)
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK097364)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords: factorial design, multicomponent intervention, intervention components, interaction effects, statistical power, resource management, experimental design, randomized controlled trials
MeSH terms: Humans, Preventive Health Services, Preventive Medicine, Research Design, Randomized Controlled Trials as Topic

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