Implementing Clinical Research Using Factorial Designs: A Primer

Timothy B. Baker, Timothy B. Baker, Stevens S. Smith, Stevens S. Smith, Daniel M. Bolt, Wei Yin Loh, Robin Mermelstein, Michael C. Fiore, Megan E. Piper, Michael C. Fiore, Megan E. Piper, Linda Marie Collins

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Factorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers’ increased and careful execution of such designs.

Original languageEnglish (US)
Pages (from-to)567-580
Number of pages14
JournalBehavior Therapy
Volume48
Issue number4
DOIs
StatePublished - Jul 1 2017

Fingerprint

Randomized Controlled Trials
Research
Research Personnel
Research Design

All Science Journal Classification (ASJC) codes

  • Clinical Psychology

Cite this

Baker, T. B., Baker, T. B., Smith, S. S., Smith, S. S., Bolt, D. M., Loh, W. Y., ... Collins, L. M. (2017). Implementing Clinical Research Using Factorial Designs: A Primer. Behavior Therapy, 48(4), 567-580. https://doi.org/10.1016/j.beth.2016.12.005
Baker, Timothy B. ; Baker, Timothy B. ; Smith, Stevens S. ; Smith, Stevens S. ; Bolt, Daniel M. ; Loh, Wei Yin ; Mermelstein, Robin ; Fiore, Michael C. ; Piper, Megan E. ; Fiore, Michael C. ; Piper, Megan E. ; Collins, Linda Marie. / Implementing Clinical Research Using Factorial Designs : A Primer. In: Behavior Therapy. 2017 ; Vol. 48, No. 4. pp. 567-580.
@article{d0fcd3e8a1954ff38ca67db9a24fcdb8,
title = "Implementing Clinical Research Using Factorial Designs: A Primer",
abstract = "Factorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers’ increased and careful execution of such designs.",
author = "Baker, {Timothy B.} and Baker, {Timothy B.} and Smith, {Stevens S.} and Smith, {Stevens S.} and Bolt, {Daniel M.} and Loh, {Wei Yin} and Robin Mermelstein and Fiore, {Michael C.} and Piper, {Megan E.} and Fiore, {Michael C.} and Piper, {Megan E.} and Collins, {Linda Marie}",
year = "2017",
month = "7",
day = "1",
doi = "10.1016/j.beth.2016.12.005",
language = "English (US)",
volume = "48",
pages = "567--580",
journal = "Behavior Therapy",
issn = "0005-7894",
publisher = "Elsevier Inc.",
number = "4",

}

Baker, TB, Baker, TB, Smith, SS, Smith, SS, Bolt, DM, Loh, WY, Mermelstein, R, Fiore, MC, Piper, ME, Fiore, MC, Piper, ME & Collins, LM 2017, 'Implementing Clinical Research Using Factorial Designs: A Primer', Behavior Therapy, vol. 48, no. 4, pp. 567-580. https://doi.org/10.1016/j.beth.2016.12.005

Implementing Clinical Research Using Factorial Designs : A Primer. / Baker, Timothy B.; Baker, Timothy B.; Smith, Stevens S.; Smith, Stevens S.; Bolt, Daniel M.; Loh, Wei Yin; Mermelstein, Robin; Fiore, Michael C.; Piper, Megan E.; Fiore, Michael C.; Piper, Megan E.; Collins, Linda Marie.

In: Behavior Therapy, Vol. 48, No. 4, 01.07.2017, p. 567-580.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Implementing Clinical Research Using Factorial Designs

T2 - A Primer

AU - Baker, Timothy B.

AU - Baker, Timothy B.

AU - Smith, Stevens S.

AU - Smith, Stevens S.

AU - Bolt, Daniel M.

AU - Loh, Wei Yin

AU - Mermelstein, Robin

AU - Fiore, Michael C.

AU - Piper, Megan E.

AU - Fiore, Michael C.

AU - Piper, Megan E.

AU - Collins, Linda Marie

PY - 2017/7/1

Y1 - 2017/7/1

N2 - Factorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers’ increased and careful execution of such designs.

AB - Factorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers’ increased and careful execution of such designs.

UR - http://www.scopus.com/inward/record.url?scp=85015026632&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85015026632&partnerID=8YFLogxK

U2 - 10.1016/j.beth.2016.12.005

DO - 10.1016/j.beth.2016.12.005

M3 - Article

C2 - 28577591

AN - SCOPUS:85015026632

VL - 48

SP - 567

EP - 580

JO - Behavior Therapy

JF - Behavior Therapy

SN - 0005-7894

IS - 4

ER -

Baker TB, Baker TB, Smith SS, Smith SS, Bolt DM, Loh WY et al. Implementing Clinical Research Using Factorial Designs: A Primer. Behavior Therapy. 2017 Jul 1;48(4):567-580. https://doi.org/10.1016/j.beth.2016.12.005