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Cross-Validating Regression Models in Marketing Research

Author

Listed:
  • Joel H. Steckel

    (New York University)

  • Wilfried R. Vanhonacker

    (INSEAD)

Abstract

In this paper, a formal test on prediction errors is developed for the cross-validation of regression models under the simple random splitting framework. Analytic as well as simulation results relate the statistical power of the test to the allocation of sample observations to estimation and validation subsets. The results indicate that splitting the data into halves is suboptimal. More observations should be used for estimation than validation. Furthermore, the proportion of the sample optimally devoted to validation is small for very limited samples ( 60). However, although the 50/50 split is suboptimal, it is not tremendously so in a wide variety of circumstances.

Suggested Citation

  • Joel H. Steckel & Wilfried R. Vanhonacker, 1993. "Cross-Validating Regression Models in Marketing Research," Marketing Science, INFORMS, vol. 12(4), pages 415-427.
    • Handle: RePEc:inm:ormksc:v:12:y:1993:i:4:p:415-427
    DOI: 10.1287/mksc.12.4.415
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    Cited by:

    1. Dwivedi, Abhishek & Merrilees, Bill, 2013. "Retail brand extensions: Unpacking the link between brand extension attitude and change in parent brand equity," Australasian marketing journal, Elsevier, vol. 21(2), pages 75-84.
    2. Sudhir Voleti & Praveen K. Kopalle & Pulak Ghosh, 2015. "An Interproduct Competition Model Incorporating Branding Hierarchy and Product Similarities Using Store-Level Data," Management Science, INFORMS, vol. 61(11), pages 2720-2738, November.
    3. Sönke Albers & Lutz Hildebrandt, 2006. "Methodische Probleme bei der Erfolgsfaktorenforschung — Messfehler, formative versus reflektive Indikatoren und die Wahl des Strukturgleichungs-Modells," Schmalenbach Journal of Business Research, Springer, vol. 58(1), pages 2-33, February.
    4. McCracken,M.W. & West,K.D., 2001. "Inference about predictive ability," Working papers 14, Wisconsin Madison - Social Systems.
    5. Kusum L. Ailawadi & Bari A. Harlam, 2009. "—Retailer Promotion Pass-Through: A Measure, Its Magnitude, and Its Determinants," Marketing Science, INFORMS, vol. 28(4), pages 782-791, 07-08.
    6. Reimer, Kerstin & Albers, Sönke, 2011. "Modeling Repeat Purchases in the Internet when RFM Captures Past Influence of Marketing," EconStor Preprints 50730, ZBW - Leibniz Information Centre for Economics.
    7. Yuqian Xu & Mor Armony & Anindya Ghose, 2021. "The Interplay Between Online Reviews and Physician Demand: An Empirical Investigation," Management Science, INFORMS, vol. 67(12), pages 7344-7361, December.
    8. Bauer, Hans H. & Fischer, Marc, 2000. "Product life cycle patterns for pharmaceuticals and their impact on R&D profitability of late mover products," International Business Review, Elsevier, vol. 9(6), pages 703-725, December.
    9. Sudhir Voleti & Pulak Ghosh, 2013. "A robust approach to measure latent, time-varying equity in hierarchical branding structures," Quantitative Marketing and Economics (QME), Springer, vol. 11(3), pages 289-319, September.
    10. Wang, Zhining & Sharma, Pratyush Nidhi & Cao, Jinwei, 2016. "From knowledge sharing to firm performance: A predictive model comparison," Journal of Business Research, Elsevier, vol. 69(10), pages 4650-4658.
    11. Voleti, Sudhir & Srinivasan, V. & Ghosh, Pulak, 2017. "An approach to improve the predictive power of choice-based conjoint analysis," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 325-335.
    12. Hema Yoganarasimhan, 2020. "Search Personalization Using Machine Learning," Management Science, INFORMS, vol. 66(3), pages 1045-1070, March.
    13. Alantari, Huwail J. & Currim, Imran S. & Deng, Yiting & Singh, Sameer, 2022. "An empirical comparison of machine learning methods for text-based sentiment analysis of online consumer reviews," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 1-19.
    14. Peter Ebbes & Dominik Papies & Harald J. van Heerde, 2011. "The Sense and Non-Sense of Holdout Sample Validation in the Presence of Endogeneity," Marketing Science, INFORMS, vol. 30(6), pages 1115-1122, November.
    15. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    16. Cepeda Carrión, Gabriel & Henseler, Jörg & Ringle, Christian M. & Roldán, José Luis, 2016. "Prediction-oriented modeling in business research by means of PLS path modeling: Introduction to a JBR special section," Journal of Business Research, Elsevier, vol. 69(10), pages 4545-4551.

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