by Michiel Bliemer » Wed Feb 12, 2020 8:16 am
With respect to estimation, you can mix numbers of levels across different attributes, you should choose the number of levels based on what makes most sense. For qualitative attributes often the number of levels is given (e.g. brands). For quantitative attributes you can choose the number of levels (e.g. price) and I would recommend choosing at least 3 levels such that you are able to estimate nonlinear effects.
With respect to design, you can also mix numbers of levels across different attributes when you are generating an efficient design, while for an orthogonal design it may be more difficult (or impossible) to find a design if the number of levels greatly vary. Orthogonal designs have been widely used in the past and this has often restricted researchers to choose the number of levels, but with more state-of-the-art efficient designs this is no longer an issue and you can essentially choose any number of levels you like. The number of rows (choice tasks) in the design should preferably be divisible by 2 and 3 in your case in order to have attribute level balance across the design, but this is not strictly necessary.
Michiel