The Effect of Level Overlap and Color Coding on Attribute Non-attendance in Discrete Choice Experiments
Objective: The aim of this study was to test the hypothesis that level overlap and color coding can mitigate or even preclude the occurrence of attribute nonattendance in discrete choice experiments. Methods: A randomized controlled experiment with five experimental study arms was designed to investigate the independent and combined impact of level overlap and color coding on respondents' attribute nonattendance. The systematic differences between the study arms allowed for a direct comparison of observed dropout rates and estimates of the average number of attributes attended to by respondents, which were obtained by using augmented mixed logit models that explicitly incorporated attribute non-attendance. Results: In the base-case study arm without level overlap or color coding, the observed dropout rate was 14%, and respondents attended, on average, only two out of five attributes. The independent introduction of both level overlap and color coding reduced the dropout rate to 10% and increased attribute attendance to three attributes. The combination of level overlap and color coding, however, was most effective: it reduced the dropout rate to 8% and improved attribute attendance to four out of five attributes. The latter essentially removes the need to explicitly accommodate for attribute non-attendance when analyzing the choice data. Conclusions: On the basis of the presented results, the use of level overlap and color coding are recommendable strategies to reduce the dropout rate and improve attribute attendance in discrete choice experiments.
|Keywords||Attribute non-attendance, Color coding, Discrete choice experiment, Level overlap|
|Persistent URL||dx.doi.org/10.1016/j.jval.2017.10.002, hdl.handle.net/1765/103006|
|Journal||Value in Health|
Jonker, M.F, Donkers, A.C.D, de Bekker-Grob, E.W, & Stolk, E.A. (2017). The Effect of Level Overlap and Color Coding on Attribute Non-attendance in Discrete Choice Experiments. Value in Health. doi:10.1016/j.jval.2017.10.002