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In ( 1), it is assumed that there are only two outcomes (denoted “success” or “failure”) and a fixed number of trials ( n). The mean and variance for the binomial random variable are and, respectively. The natural distribution for modeling these types of binary data is the binomial distribution given by A binary outcome is an outcome whose unit can take on only two possible states “0” and “1.” This success/failure response variable could be heart disease (Yes/No), patient condition (Good/Critical), how often patient feel depressed (Never/Often), and so on.
BAYESIAN IN COMPREHENSIVE META ANALYSIS TRIAL
Sometimes in these studies, the clinical trial end point may be the success or failure of the treatment. IntroductionĬonsider a clinical trial where a pharmaceutical company wants to test a new drug against a currently existing drug. We illustrate the methods using actual data arising from two-arm clinical trials on preventing mortality after myocardial infarction. The Bayesian inference is carried out using Markov Chain Monte Carlo (MCMC) methods. We then examine the suitability of a normal approximation to the posterior distribution obtained via a Taylor series expansion. We discuss the development of likelihood, the prior, and the posterior distributions of parameters of interest. We consider a Bayesian approach for assessing hypotheses of equivalence in two-arm trials with binary Data.