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A CHECKLIST FOR CONJOINT ANALYSIS APPLICATIONS IN HEALTH: REPORT OF THE ISPOR CONJOINT ANALYSIS GOOD ... - page 8 / 17

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Attribute levels are usually combined into profiles in the conjoint tasks using an orthogonal design. However, if attributes are correlated, an orthogonal design could results in illogical combinations of attribute levels in a given profile in the conjoint task. For example, if one attribute defining a profile is the need for medication (no medication required or 2 tablets a day), it makes no sense to combine certain levels of this attribute with certain levels of an attribute describing the side effects of the medication (mild or severe) because some profiles would include a combination of the “no medication required” level of the need for medication attribute with the “severe” level of the side effect attribute.

iii. Construction of tasks

Conjoint tasks can be assembled in a number of different ways, and hence it is important to ask, “Was the construction of the conjoint tasks appropriate?”

First, each profile that subjects are asked to evaluate could include the full set of attributes included in the study (a full-profile task) or a subset of the attributes included in the study (a partial-profile task). Prior to constructing conjoint tasks with full profiles, researchers should determine, through qualitative research or quantitative pilot tests whether or not subjects can reasonably evaluate the full profiles or if they will employ simplifying heuristics such as focusing on only a few attributes while ignoring others when completing the conjoint tasks. If this happens, researchers learn nothing about subject preferences among the attributes that the subjects ignore and the importance of the attributes on which subjects focus likely will be overstated. If each conjoint task contains a partial profile, researchers must understand the effect of omitting some attributes in some conjoint tasks while omitting other attributes in different conjoint tasks. The way in which certain attributes are omitted can introduce biases in the results of the study.

The number of conjoint tasks often varies from study to study depending on the type and difficulty of each conjoint task. In some studies, subjects may be presented with a set of many alternative profiles and asked to order or rank the profiles from most preferred to least preferred. In this type of study, subjects often complete only one conjoint task. In other studies, profiles are grouped in sets of two or three and subjects are asked to rate, rank, or choose among these alternatives. Because each conjoint task includes only a small subset of the overall number of potential profiles, subjects often are asked to complete multiple conjoint tasks. In this case, researchers should justify both the number of profiles in each conjoint task and the number of conjoint tasks included in the data collection instrument.

iv. Experimental design

Experimental design is the process of systematically manipulating the attribute levels to create the profiles and conjoint tasks, hence it is important to ask, “Was the choice of experimental design justified and evaluated?”

The aim of an experimental design is to create a set of conjoint tasks that will yield as much statistical information as possible to estimate the parameters of the underlying preference model (usually preference weights for all attribute levels) with the most precision (27-28). There are several design properties that should be considered when choosing an experimental design in a conjoint study. A design is orthogonal if all effects can be estimated independently of all other effects (the effects are uncorrelated). A design is balanced when each level of an attribute is presented the same number of times across the set of conjoint tasks. Furthermore, efficiency is a

ISPOR Conjoint Analysis in Health Task Force Report

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