Bayes Estimation in Meta-analysis using a linear model theorem
نویسندگان
چکیده
A Hierarchical Bayesian meta-analysis model developed by Dumouchel is derived by implementing the General Bayesian Linear model (GBLM) theorem. The aim is to obtain the joint posterior distribution of all parameters in the model. Simulation study is conducted to confirm the estimation of all parameters of interest. Results show parameter estimates as close to the true values indicating parameter stability.
منابع مشابه
Bayes Estimation for a Simple Step-stress Model with Type-I Censored Data from the Geometric Distribution
This paper focuses on a Bayes inference model for a simple step-stress life test using Type-I censored sample in a discrete set-up. Assuming the failure times at each stress level are geometrically distributed, the Bayes estimation problem of the parameters of interest is investigated in the both of point and interval approaches. To derive the Bayesian point estimators, some various balanced lo...
متن کاملBayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function
In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In th...
متن کاملComputer Modeling Strategies for Meta-analysis
Over the past decade, meta-analyses have played an increasingly important role in summarizing clinical information and informing policy. Consequently, a new generation of meta-analysts have come forth and the demand for a streamlined modeling approach has emerged. In particular, compared to linear model estimation, many aspects of selecting and tting models for meta-analysis involve nonstandard...
متن کاملClassic and Bayes Shrinkage Estimation in Rayleigh Distribution Using a Point Guess Based on Censored Data
Introduction In classical methods of statistics, the parameter of interest is estimated based on a random sample using natural estimators such as maximum likelihood or unbiased estimators (sample information). In practice, the researcher has a prior information about the parameter in the form of a point guess value. Information in the guess value is called as nonsample information. Thomp...
متن کاملBayes Interval Estimation on the Parameters of the Weibull Distribution for Complete and Censored Tests
A method for constructing confidence intervals on parameters of a continuous probability distribution is developed in this paper. The objective is to present a model for an uncertainty represented by parameters of a probability density function. As an application, confidence intervals for the two parameters of the Weibull distribution along with their joint confidence interval are derived. The...
متن کامل