The CVA designer uses a computer search technique to find D-efficient designs, given a certain conjoint design, any prohibitions (for level by level combinations or due to utility balance constraints), and a requested number of conjoint profiles.
D-efficiency is described in the article by Kuhfeld, Tobias, and Garratt (1994), "Efficient Experimental Design with Marketing Research Applications," Journal of Marketing Research, 31 (November), 545-557.
Paraphrasing the article, D-efficiency is a function of the determinant of the X'X matrix, given by the formula:
| where ND | = number of tasks |
| p | = number of attributes |
| X | = the design matrix using orthogonal coding |
If a design is orthogonal and balanced (each level within an attribute shown an equal number of times), then it has optimum efficiency.
The D-efficiency measures the goodness of the design relative to the hypothetical orthogonal design. A perfect design will be both orthogonal and balanced and will result in an efficiency of 1.0. However, an orthogonal design is not always possible, given the number of attribute levels and requested number of tasks. A final efficiency of less than 1.0 may still indicate a satisfactory design.
User-Specified Designer Controls
CVA generates an initial pool of conjoint profiles equal to ten times the requested number. It repeats the search process within that candidate pool equal to ten times as many questionnaire versions that are requested. Some users may wish to over-ride these limits to either speed up the process, or to let CVA spend an even greater amount of time searching for the most efficient design. You can override the defaults by clicking the Show Advanced Settings button and modifying the fields that appear. For larger CVA designs, a task pool multiplier of 100 or more often will lead to finding more efficient designs faster.