Robustness and sensitivity of conjoint analysis versus multiple linear regression analysis

Fahri Karakaya and Abhrawashyu Awasthi

International Journal of Data Analysis Techniques and Strategies, 2014, vol. 6, issue 2, 121-136

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.

Keywords: conjoint analysis; sensitivity analysis; multiple linear regression analysis; robust statistics; orthogonal data; robustness. (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:ids:injdan:v:6:y:2014:i:2:p:121-136

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