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support.CEs (version 0.4-1)

support.CEs-package: Basic functions for supporting an implementation of choice experiments

Description

The package support.CEs provides seven basic functions that support an implementation of choice experiments. These include the following functions: two for creating a choice experiment design, which is based on orthogonal main-effect arrays; one for converting a choice experiment design into questionnaire format; one for converting a choice experiment design into a design matrix; one for making the data set suitable for a conditional logit model analysis using the function clogit in the package survival, or for a binary choice model analysis using the function glm in the package stats; one for calculating goodness-of-fit measures for an estimated model; and one for calculating the marginal willingness to pay for the attributes and/or levels of the estimated model. Version 0.3-0 and later versions of this package are also available for binary choice experiments.

Arguments

tabular

  • c
  • lcc
  • c
  • lcc
  • c

tab

  • Alternative 1 Alternative 2 Attribute A a2 a1 Attribute B b3 b2 Attribute C c1 c3
  • Alternative 1 Alternative 2 Attribute A a3 a2 Attribute B b2 b2 Attribute C c1 c2

itemize

  • I select alternative 1.

item

  • I select alternative 2.
  • I select none of these.
  • I select alternative 2.
  • I select none of these.

Details

The terms in this manual are defined as follows. An "attribute" is a characteristic or feature of an alternative. A "level" or "attribute level" represents the value of an attribute. One attribute can have two or more levels. An "alternative" is a combination of attributes; that is, one alternative can have two or more attributes. For example, when applying choice experiments to marketing research, the alternatives would refer to the "goods" or "services" that respondents are asked to select. A "choice set" refers to a set of alternatives available to individuals. One choice set includes two or more alternatives, including an opt-out alternative, if one exists. In a choice experiment question, respondents are usually asked to select the most preferred alternative from a choice set; therefore, one choice set constitutes a choice experiment question. A "choice experiment design" refers to a collection of individual choice sets.

The following shows an example of a choice experiment design. The choice experiment design includes a total of 9 choice sets (Q1 to Q9). Each choice set (question) consists of three alternatives ("Alternative 1," "Alternative 2," and "None of these" option). "Alternative 1" and "Alternative 2" each consist of three attributes: an attribute A with the three levels of "a1," "a2," and "a3"; an attribute B with the three levels of "b1," "b2," and "b3"; and an attribute C with the three levels of "c1," "c2," and "c3."

c{ }

Q1. Please select your most preferred alternative from the following:

lcc{ Alternative 1 Alternative 2 Attribute A a2 a3 Attribute B b2 b3 Attribute C c2 c3 }

  • I select alternative 1.
I select alternative 2. I select none of these.

References

Aizaki, H. (2012) Basic Functions for Supporting an Implementation of Choice Experiments in R. Journal of Statistical Software, Code Snippets, 50(2), 1--24. http://www.jstatsoft.org/v50/c02/

See Also

oa.design, clogit, glm