The %ChoicEff autocall macro finds efficient experimental designs for choice experiments and evaluates choice designs.
The %MktAllo autocall macro manipulates data for an allocation choice experiment.
The %MktBal autocall macro creates factorial designs by using an algorithm that ensures that the design is perfectly balanced, or as close to perfectly balanced as possible.
The %MktBIBD autocall macro finds balanced incomplete block designs (BIBDs).
The %MktBlock autocall macro blocks a choice design or an ordinary linear experimental design.
The %MktBSize autocall macro suggests sizes for balanced incomplete block designs.
The %MktDes autocall macro creates efficient experimental designs.
The %MktDups autocall macro detects duplicate choice sets and duplicate alternatives within generic choice sets.
The %MktEval autocall macro evaluates an experimental design for a linear model and reports on balance and orthogonality.
The %MktEx autocall macro creates efficient factorial designs.
The %MktKey autocall macro creates expanded lists of variable names and creates an output data set.
The %MktLab autocall macro processes an experimental design and assigns the final variable names and levels.
The %MktMDiff autocall macro analyzes MaxDiff (maximum difference or best-worst) data.
The %MktMerge autocall macro merges a data set that contains a choice design with choice data.
The %MktOrth autocall macro lists some of the 100% orthogonal main-effects plans that the %MktEx macro can generate.
The %MktPPro autocall macro makes optimal partial-profile designs from block designs and orthogonal arrays.
The %MktRoll autocall macro constructs a choice design from a linear arrangement.
The %MktRuns autocall macro suggests reasonable sizes for experimental designs.
The %PHChoice autocall macro customizes the output from PROC PHREG for choice modeling.