Effects coding in discrete choice experiments.

By Mickael Bech, D. Gyrd-Hansen. Health Economics, 2005

628 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Decision Sciences, Marketing

View Paper: https://www.semanticscholar.org/paper/98959d359a71804f509c84cbef11d80550034e17

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Citations in the corpus

Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software (2017, neutral): “priate as long as interpreted appropriately [44, 45].”
Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force. (2016, methodology): “See Bech and Gyrd-Hansen [45] for further discussion of differences between effects coding and dummy-variable coding.”
Consumer willingness to pay for traditional food products (2016, background): “As suggested by Bech and Gyrd-Hansen (2005), the base levels (no certification, 50% mangalitza share and farmers’ market, for each of the three attributes) were set equal to the negative sum of the estimated coefficients of the other levels within an attribute. Consequently, effects for all levels c”
Land-use planning and public preferences: What can we learn from choice experiment method? (2007, methodology): “With dummy coding the coefficient estimates of attribute variables are correlated to the intercept of the regression (Bech and Gyrd-Hansen, 2005), which corresponds to the alternative dummy code in the conditional logit model.”
Modeling heterogeneity in consumer preferences for select food safety attributes in China (2011, background): “The data was effects coded to eliminate confounding effects between the constant and the attributes (Bech and Gyrd-Hansen, 2005).”
Conducting Discrete Choice Experiments to Inform Healthcare Decision Making (2012, methodology): “It is also related to experimental have used effects codes;[30,31,35] the importance of design since the number of observations depends on using these codes is highlighted by Bech and Gyrdthe number of choice sets per respondent and num- Hansen.[71] It is worth noting that the estimate of the ber of”
Grocery Shopping Preferences during the COVID-19 Pandemic (2020, methodology): “While binary coding is the conventional approach with choice experiment data, we use effect coding to facilitate robust estimation and interpretation of all the attributes and their levels [29,30].”