Using a two-part mixed-effects model for understanding daily, individual-level media behavior

This study supports a strategic analytics proposal, namely that there is conceptual and practical utility in applying a two-part mixed-effects model for understanding individual differences in daily media use. Individual-level daily diary measures of media use typically contain information about a p...

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Published inJournal of marketing analytics Vol. 7; no. 4; pp. 234 - 250
Main Authors Blozis, Shelley A., Villarreal, Ricardo, Thota, Sweta, Imparato, Nicholas
Format Journal Article
LanguageEnglish
Published London Palgrave Macmillan UK 01.12.2019
Palgrave Macmillan
Subjects
Behavior
Business and Management
Consumers
Data collection
Diaries
Market analysis
Marketing
Media
Media planning & buying
Original Article
Tactics
Time use
Within-subjects design
Media
TV
Repeated measures
Frequency versus reach
Mixed-effects models
Diary data
Online AccessGet full text
ISSN2050-3318
2050-3326
DOI10.1057/s41270-019-00062-7

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Abstract This study supports a strategic analytics proposal, namely that there is conceptual and practical utility in applying a two-part mixed-effects model for understanding individual differences in daily media use. Individual-level daily diary measures of media use typically contain information about a person’s likeliness to use media, extent of usage, and variation in use across days that, taken together, can provide data for evaluating media behavior that is otherwise masked by using aggregate measures. The statistical framework developed and demonstrated here focuses on these three metrics. The approach, applied to daily diary measures of television use in a large, representative U.S. sample, yields results that add value when weighing media strategies centered on the twin tactics of reach and frequency. The implications for the proposed analytic strategy are discussed.
AbstractList This study supports a strategic analytics proposal, namely that there is conceptual and practical utility in applying a two-part mixed-effects model for understanding individual differences in daily media use. Individual-level daily diary measures of media use typically contain information about a person’s likeliness to use media, extent of usage, and variation in use across days that, taken together, can provide data for evaluating media behavior that is otherwise masked by using aggregate measures. The statistical framework developed and demonstrated here focuses on these three metrics. The approach, applied to daily diary measures of television use in a large, representative U.S. sample, yields results that add value when weighing media strategies centered on the twin tactics of reach and frequency. The implications for the proposed analytic strategy are discussed.
Author Blozis, Shelley A.
Imparato, Nicholas
Villarreal, Ricardo
Thota, Sweta
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  organization: Department of Marketing, School of Management, University of San Francisco
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10.1287/mksc.1120.0759
10.1080/07350015.1983.10509330
10.2501/S0021849908080392
10.1177/0962280215590284
10.1093/biomet/70.1.1
10.1198/016214501753168389
10.2501/JAR-2017-004
10.1080/02650487.2015.1022975
10.1080/02650487.2017.1335010
10.1080/00913367.2016.1183244
10.1111/j.0006-341X.2000.00909.x
10.2307/1913974
10.1509/jmr.12.0241
10.1080/00913367.2015.1018460
10.2307/2529876
10.1007/978-88-470-2871-5_12
10.1007/978-1-4899-2873-3
10.1016/j.jhealeco.2009.11.010
10.1002/9780470510445
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Repeated measures
Frequency versus reach
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References_xml – reference: CookRDWeisbergSDiagnostics for heteroscedasticity in regressionBiometrika198370111010.1093/biomet/70.1.1
– reference: OlsenMKSchaferJLA two-part random effects model for semicontinuous longitudinal dataJournal of the American Statistical Association20019645473074510.1198/016214501753168389
– reference: LairdNMWareJHRandom-effects models for longitudinal dataBiometrics198238496397410.2307/2529876
– reference: XuSBlozisSASensitivity analysis of mixed models for incomplete longitudinal dataJournal of Educational and Behavioral Statistics201136223725610.3102/1076998610375836
– reference: TobinJEstimation of relationships for limited dependent variablesEconometrica1958261243610.2307/1907382
– reference: CarrollRJRuppertDTransformation and Weighting in Regression1988New YorkChapman & Hall10.1007/978-1-4899-2873-3
– reference: CheonHJFraserFRNguyenTKFamily-based treatment for obesity in tweens: A three-year longitudinal follow-up studyInternational Journal of Advertising201837454856710.1080/02650487.2017.1339583
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– reference: La FerleCLeeWNCan English language media connect with ethnic audiences? Ethnic minorities’ media use and representation perceptionsJournal of Advertising Research200545114015310.1017/S002184990505004X
– reference: DuanNManningWGJrMorrisCNNewhouseJPA comparison of alternative models for the demand for medical careJournal of Business & Economic Statistics198312115126
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– reference: HarveyACEstimating regression models with multiplicative heteroscedasticityEconometrica197644346146510.2307/1913974
– reference: MinYAgrestiAModeling nonnegative data with clumping at zero: a surveyJournal of the Iranian Statistical Society200211–2733
– reference: Nelson-FieldKRiebeESharpBWhat’s not to “like?”: Can Facebook fan base give a brand the advertising reach it needs?Journal of Advertising Research201252226226910.2501/JAR-52-2-262-269
– reference: O’GuinnTCAllenCTClose ScheinbaumASemenikRJAdvertising and Integrated Brand Promotion2019BostonCengage Learning Inc
– reference: XuSBlozisSAVandewaterEOn fitting a multivariate two-part latent growth modelStructural Equation Modeling201421113114810.1080/10705511.2014.856699
– reference: KellyJSJonesSKThe IMC Handbook: Readings & Cases in Integrated Marketing Communications2012ChicagoRamcom Communications
– reference: MoraJDSocial context and advertising effectiveness: a dynamic studyInternational Journal of Advertising201635232534410.1080/02650487.2015.1022975
– reference: MolenberghsGKenwardMMissing Data in Clinical Studies2007West SussexWiley10.1002/9780470510445
– reference: XingDHuangYChenHZhuYDagneGABaldwinJBayesian inference for two-part mixed-effects model using skew distributions, with application to longitudinal semicontinuous alcohol dataStatistical Methods in Medical Research20172641838185310.1177/0962280215590284
– reference: KazakovaSCaubergheVHuddersLLabytCThe impact of media multitasking on the cognitive and attitudinal response to television commercials: The moderating role of type of advertising appealJournal of Advertising201645440341610.1080/00913367.2016.1183244
– reference: LarsenKPetersenJHBudtz-JorgensenEEndahlLInterpreting parameters in the logistic regression model with random effectsBiometrics200056390991410.1111/j.0006-341X.2000.00909.x
– reference: Wolfinger, R.D. 2000. Fitting nonlinear mixed models with the new NLMIXED procedure, Paper 287, SAS Institute Inc., Proceedings of the Twenty-Fifth Annual SAS Users Group International Conference Cary, NC: SAS Institute Inc.
– reference: AdAge. 2017. Marketing Fact Pack 2018 http://adage.com/d/resources/resources/whitepaper/marketing-fact-pack-2018.
– reference: SchmidtSEisendMAdvertising repetition: a meta-analysis on effective frequency in advertisingJournal of Advertising201544441542810.1080/00913367.2015.1018460
– reference: PrecourtGWhy tv still mattersJournal of Advertising Research20175711210.2501/JAR-2017-004
– reference: GottardAStanghelliniECapobiancoRGrigolettoMFrancescoLPetroneSSemicontinuous regression models with skew distributionComplex Models and Computational Methods in Statistics2013Verlag-MailandSpringer14916010.1007/978-88-470-2871-5_12
– reference: DanaherPJDaggerTSComparing the relative effectiveness of advertising channels: a case study of a multimedia blitz campaignJournal of Marketing Research201350451753410.1509/jmr.12.0241
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Snippet This study supports a strategic analytics proposal, namely that there is conceptual and practical utility in applying a two-part mixed-effects model for...
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SubjectTerms Behavior
Business and Management
Consumers
Data collection
Diaries
Market analysis
Marketing
Media
Media planning & buying
Original Article
Tactics
Time use
Within-subjects design
Title Using a two-part mixed-effects model for understanding daily, individual-level media behavior
URI https://link.springer.com/article/10.1057/s41270-019-00062-7
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