Robustness and sensitivity of conjoint analysis versus multiple linear regression analysis

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.

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Year of publication:	2014
Authors:	Karakaya, Fahri ; Awasthi, Abhrawashyu
Published in:	International Journal of Data Analysis Techniques and Strategies. - Inderscience Enterprises Ltd, ISSN 1755-8050. - Vol. 6.2014, 2, p. 121-136
Publisher:	Inderscience Enterprises Ltd
Subject:	conjoint analysis \| sensitivity analysis \| multiple linear regression analysis \| robust statistics \| orthogonal data \| robustness

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011015150