Design of Experiments in Biostatistics: Design of experiments (DOE) is a branch of applied statistics that is used for conducting scientific studies of a system or process in which input variables (X1 X2 X3, …) are manipulated to investigate its effects on a measured response variable (y1 y2 y3,…). It is one of the important data collection and analysis tools that can be used for planning, conducting analyzing, and interpreting controlled tests in a different experimental situation. DOE tools can be used in various situations such as de for comparisons, variable screening, transfer function identification, optimization, and robust design. The applications of DOE have been expanded across many industrial and clinical trials for new product development. It is used for multiple comparisons to select the best option that uses F-test, t-test, or z-test. Variable screening is the two-level factorial design used to select important variables among many that affect the performances of a system or process. The relationship between the input variables and output variables can be used for further performance exploration of the system via, transfer function. A transfer function can be used for optimization by moving the experiment to the optimum setting of the variables.
The design of experiments can be performed and analyzed with the help of suitable statistical software. DOE software can be used for setting and analyzing general factorial, two-level factorial, fractional factorial, Plackett-Burman designs. It is also used for identifying key factors for process, optimizations, screening for critical factors, analyzing process factors or mixture components, etc. It is also used to visualize response surfaces by rotating 3D plots.
Today, DOE software is the most valuable tool for engineers, scientists, biologists, and new rug developers. Computer software is available for designing experiments from various software companies and it includes packages such as JMP, Minitab, Design-Expert, Statistical, SPASS, SAS, stat graphics, R, Microsoft Excel, etc.
Minitab and statistics are the most popular packages that are equipped with user-friendly interfaces and very good graphics output. Microsoft excel has also commonly used software for DOE design and analysis. DOE software is the fastest and most cost-effective way to design different experiments, increase productivity, and face challenges in new drug development.
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