2012
DOI: 10.18637/jss.v050.c02
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Basic Functions for Supporting an Implementation of Choice Experiments inR

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Cited by 113 publications
(103 citation statements)
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“…The utility coefficients (␤ 1 -␤ 6 ) were calculated using clogit function in the support.CEs package in R (Aizaki, 2012). Qualitative attributes were coded as dummy variables, and the monetary parameter (i.e.…”
Section: Discussionmentioning
confidence: 99%
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“…The utility coefficients (␤ 1 -␤ 6 ) were calculated using clogit function in the support.CEs package in R (Aizaki, 2012). Qualitative attributes were coded as dummy variables, and the monetary parameter (i.e.…”
Section: Discussionmentioning
confidence: 99%
“…A choice set was generated by randomly selecting one alternative from each set of N alternatives. The selection process was repeated without replacement until all alternatives were assigned to choice sets (Aizaki, 2012). The number of 36 choice sets of two alternatives was suggested from R output.…”
Section: Experiments Designmentioning
confidence: 99%
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“…The experimental design of the overall survey is based on the L MA design 1 generated internally from the support.CEs program [11], where the experimental design is directly from the orthogonal main effects plan [12]. This experimental design is generally larger than most orthogonal main effects plan for DCEs [13], which the authors mitigate through effective separation of the choice sets into multiple blocks; subsets of choice sets.…”
Section: Experimental Designmentioning
confidence: 99%
“…Based on a sample of 300 responses 3 , the following esti-mations were run using the "support.CEs" program [11]. After the survey responses are encoded into a form legible by the program and supplementing it with previously generated survey design information, the commands are run to provide estimates for Malaysian home buyers' WTP for sustainable features using the conditional logit framework, shown in Table 4.…”
Section: Home Buyer Stated Preferencesmentioning
confidence: 99%