It can be used to answer questions such as "How far can a carton of eggs fall, on average, before one breaks?"
The Neyer test is useful in any situation when you wish to determine the average amount of a given stimulus needed in order to trigger a response.
This method has replaced the earlier Bruceton analysis or "Up and Down Test" that was devised by Dixon and Mood in 1948 to allow computation with pencil and paper.
Dror and Steinberg (2008) suggest another experimental design method which is more efficient than Neyer's, by enabling the usage of a D-optimal design criterion from the outset of the experiment.
Furthermore, their method is extended to deal with situations which are not handled by previous algorithms, including extension from fully sequential designs (updating the plan after each observation) to group-sequential designs (any partition of the experiment to blocks of numerous observations), from a binary response ("success" or "failure") to any generalized linear model, and from the univariate case to the treatment of multiple predictors (such as designing an experiment to test a response in a medical treatment where the experimenters changes doses of two different drugs).