Several applications, such as risk assessment within REACH or drug discovery, require reliable methods for the design of experiments and efficient testing strategies. Keeping the number of experiments as low as possible is important from both a financial and an ethical point of view, as exhaustive testing of compounds requires significant financial resources and animal lives. With a large initi...

Abstract This study aimed to obtain the optimum formula of Chlorella milk with D-Optimal Mixture Design and determine consumer preference for formula. research method was divided into formulation response design, hedonic test, analysis, optimization, verification The determined based on highest score taste. Two solutions were obtained, it found that 0.40% + 0.05% vanillin 4.55% sugar most prefe...

We study the consistency of parameter estimators in adaptive designs generated by a onestep ahead D-optimal algorithm. We show that when the design space is finite, under mild conditions the least-squares estimator in a nonlinear regression model is strongly consistent and the information matrix evaluated at the current estimated value of the parameters strongly converges to the D-optimal matri...

A method of data collection is presented that unites the efficiency of mass testing with the ease of instant electronic data collection that is typical of computer-based experiments run on individual participants. A wireless response system (WRS), originally designed as a teaching tool, is used to replicate three classic and robust effects from the memory literature (effects of false memory, le...

OBJECTIVES Discrete choice experiments (DCEs) are routinely used to elicit patient preferences to improve health outcomes and healthcare services. While many fractional factorial designs can be created, some are more statistically optimal than others. The objective of this simulation study was to investigate how varying the number of (1) attributes, (2) levels within attributes, (3) alternative...