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Robustness and sensitivity of conjoint analysis versus multiple linear regression analysis

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  • Fahri Karakaya
  • Abhrawashyu Awasthi

Abstract

This study compares the robustness of conjoint analysis versus multiple linear regression when using orthogonal data. The explained variance (R²) by four independent variables was utilised to test the robustness of the regression analysis while Pearson's R and Kendall's tau were used for testing conjoint method. The results indicate that the two methods produce somewhat different results and conjoint analysis is more robust compared to regression.

Suggested Citation

  • Fahri Karakaya & Abhrawashyu Awasthi, 2014. "Robustness and sensitivity of conjoint analysis versus multiple linear regression analysis," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 6(2), pages 121-136.
    • Handle: RePEc:ids:injdan:v:6:y:2014:i:2:p:121-136
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    Cited by:

    1. Shahzad Nazir & Muhammad Asif & Shahbaz Ahmad & Faisal Bukhari & Muhammad Tanvir Afzal & Hanan Aljuaid, 2020. "Important citation identification by exploiting content and section-wise in-text citation count," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-19, March.
    2. Mohamed Akli Achabou, 2021. "Is animal welfare a central issue for consumers of luxury goods?," Natural Resources Forum, Blackwell Publishing, vol. 45(1), pages 18-36, February.

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