Experimental Design: A Bayesian Perspective
نویسنده
چکیده
This entry provides an overview of experimental design using a Bayesian decision-theoretic framework. Scientific experimentation requires decisions about how an experiment will be conducted and analyzed. Such decisions depend on the goals and purpose of the experiment, but certain choices may be restricted by available resources and ethical considerations. Prior information may be available from earlier experiments or from conjectures which motivate the investigation. The Bayesian approach provides a coherent framework where prior information and uncertainties regarding unknown quantities can be combined to find an experimental design that optimizes the goals of the experiment.
منابع مشابه
The Bayesian View of Extreme Events
A key step in “Designing for the Consequences of Hazard” is choosing which hazards to design for. This paper argues that the Bayesian perspective is the rational and prudent framework.
متن کاملWhere do priors and causal models come from? An experimental design perspective
In this pedagogical note, we treat prior elicitation and experimental design within a common decision making framework. This is contrary to the standard practice of assuming that priors are already available when performing Bayesian experimental design. We argue instead that these processes are intertwined. We demonstrate our decision-theoretic stance in the setting of learning a causal Bayesia...
متن کاملBayesian Sample Size Determination for Joint Modeling of Longitudinal Measurements and Survival Data
A longitudinal study refers to collection of a response variable and possibly some explanatory variables at multiple follow-up times. In many clinical studies with longitudinal measurements, the response variable, for each patient is collected as long as an event of interest, which considered as clinical end point, occurs. Joint modeling of continuous longitudinal measurements and survival time...
متن کاملBayesian Sample size Determination for Longitudinal Studies with Continuous Response using Marginal Models
Introduction Longitudinal study designs are common in a lot of scientific researches, especially in medical, social and economic sciences. The reason is that longitudinal studies allow researchers to measure changes of each individual over time and often have higher statistical power than cross-sectional studies. Choosing an appropriate sample size is a crucial step in a successful study. A st...
متن کاملAn Efficient Bayesian Optimal Design for Logistic Model
Consider a Bayesian optimal design with many support points which poses the problem of collecting data with a few number of observations at each design point. Under such a scenario the asymptotic property of using Fisher information matrix for approximating the covariance matrix of posterior ML estimators might be doubtful. We suggest to use Bhattcharyya matrix in deriving the information matri...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007