Evidence map›Paper›PMID 34632281›Full record

ArticlePerspectives on behavior science2021

Applying Mixed-Effects Modeling to Behavioral Economic Demand: An Introduction.

Brent A Kaplan, Christopher T Franck, Kevin McKee, Shawn P Gilroy, Mikhail N Koffarnus

Abstract read
In one paragraph

Article in Perspectives on behavior science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Review
  11. Hypothetical Purchase Task Metrics Predict Responding on an Incentivized Purchase Task for Full and Reduced Nicotine Cigarettes.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
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  13. Article
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  17. Review
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  19. Examining Demand and Substitutability of Usual Brand Little Cigars/Cigarillos and Cigarettes in Young Adults Who Dual Use.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024
    Article
  20. Cannabis demand and use among veterans: A prospective examination.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Brent A KaplanDepartment of Family and Community Medicine, University of Kentucky, 2195 Harrodsburg Rd., Suite 125, Lexington, KY 40504 USA.ORCID 0000-0002-3758-6776
Christopher T FranckDepartment of Statistics, Virginia Tech, Blacksburg, VA USA.
Kevin McKeeDepartment of Statistics, Virginia Tech, Blacksburg, VA USA.ORCID https://orcid.org/0000-0003-0803-9826
Shawn P GilroyDepartment of Psychology, Louisiana State University, Baton Rouge, LA USA.ORCID https://orcid.org/0000-0002-1097-8366
Mikhail N KoffarnusDepartment of Family and Community Medicine, University of Kentucky, 2195 Harrodsburg Rd., Suite 125, Lexington, KY 40504 USA.ORCID https://orcid.org/0000-0002-7923-7734

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Behavioral economic demand methodology is increasingly being used in various fields such as substance use and consumer behavior analysis. Traditional analytical techniques to fitting demand data have proven useful yet some of these approaches require preprocessing of data, ignore dependence in the data, and present statistical limitations. We term these approaches "fit to group" and "two stage" with the former interested in group or population level estimates and the latter interested in individual subject estimates. As an extension to these regression techniques, mixed-effect (or multilevel) modeling can serve as an improvement over these traditional methods. Notable benefits include providing simultaneous group (i.e., population) level estimates (with more accurate standard errors) and individual level predictions while accommodating the inclusion of "nonsystematic" response sets and covariates. These models can also accommodate complex experimental designs including repeated measures. The goal of this article is to introduce and provide a high-level overview of mixed-effects modeling techniques applied to behavioral economic demand data. We compare and contrast results from traditional techniques to that of the mixed-effects models across two datasets differing in species and experimental design. We discuss the relative benefits and drawbacks of these approaches and provide access to statistical code and data to support the analytical replicability of the comparisons. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40614-021-00299-7.

Indexed as

behavioral economicsbehavioral sciencedemandmixed-effects modelmultilevel modeloperantpurchase taskR programming language

Identifiers

PMID34632281
PMCPMC8476685

What OpenQuestion holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.