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Working papers / Faculty of Applied Economics, Universiteit Antwerpen
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Comparing different sampling schemes for approximating the integrals involved in the semi-Bayesian optimal design of choice experiments
Yu, Jie
;
Goos, Peter
;
Vandebroek, Martina
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2008
Persistent link: https://www.econbiz.de/10003981800
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2
Models and optimal designs for conjoint choice experiments including a no-choice option
Vermeulen, Bart
(
contributor
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Goos, Peter
(
contributor
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2007
Persistent link: https://www.econbiz.de/10003621822
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3
A hierarchical Bayesian approach to robust parameter design
Goegebeur, Yuri
(
contributor
);
Goos, Peter
(
contributor
); …
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2007
Persistent link: https://www.econbiz.de/10003623807
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4
Efficient conjoint choice designs in the presence of respondent heterogeneity
Yu, Jie
(
contributor
);
Goos, Peter
(
contributor
); …
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2007
Persistent link: https://www.econbiz.de/10003624525
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5
Rank-order conjoint experiments : efficiency and design
Vermeulen, Bart
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contributor
);
Goos, Peter
(
contributor
); …
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2007
Persistent link: https://www.econbiz.de/10003625829
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6
Optimal two-level conjoint designs for large numbers of attributes
Kessels, Roselinde
(
contributor
);
Goos, Peter
(
contributor
); …
-
2006
Persistent link: https://www.econbiz.de/10003618060
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7
Recommendations on the use of Bayesian optimal designs for choice experiments
Kessels, Roselinde
;
Jones, Bradley
;
Goos, Peter
; …
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2006
Persistent link: https://www.econbiz.de/10003618075
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8
Efficient and robust willingness-to-pay designs for choice experiments : some evidence from simulations
Vermeulen, Bart
;
Goos, Peter
;
Scarpa, Riccardo
; …
-
2008
Persistent link: https://www.econbiz.de/10003976959
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9
Design criteria to develop choice experiments to measure the WTP accurately
Vermeulen, Bart
;
Goos, Peter
;
Scarpa, Riccardo
; …
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2008
Persistent link: https://www.econbiz.de/10003977325
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10
A comparison of different Bayesian design criteria to compute efficient conjoint choice experiments
Yu, Jie
;
Goos, Peter
;
Vandebroek, Martina
-
2008
Persistent link: https://www.econbiz.de/10003977597
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