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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
A Group Acceptance Sampling Plans For Lifetimes Following A Marshall-Olkin Extended Exponential Distribution, G. S. Rao
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, a group acceptance sampling plan is developed for a truncated life test when the lifetime of an item follows the Marshall-Olkin extended exponential distribution. The minimum number of groups required for a given group size and the acceptance number is determined when the consumer’s risk and the test termination time are specified. The operating characteristic values, according to various quality levels, are found and the minimum ratios of the true average life to the specified life at the specified producer’s risk are obtained. The results are explained with examples.
Frequentist Evaluation Of Group Sequential Clinical Trial Designs, Scott S. Emerson, John M. Kittelson, Daniel L. Gillen
Frequentist Evaluation Of Group Sequential Clinical Trial Designs, Scott S. Emerson, John M. Kittelson, Daniel L. Gillen
UW Biostatistics Working Paper Series
Group sequential stopping rules are often used as guidelines in the monitoring of clinical trials in order to address the ethical and efficiency issues inherent in human testing of a new treatment or preventive agent for disease. Such stopping rules have been proposed based on a variety of different criteria, both scientific (e.g., estimates of treatment effect) and statistical (e.g., frequentist type I error, Bayesian posterior probabilities, stochastic curtailment). It is easily shown, however, that a stopping rule based on one of those criteria induces a stopping rule on all other criteria. Thus the basis used to initially define a …
Bayesian Evaluation Of Group Sequential Clinical Trial Designs, Scott S. Emerson, John M. Kittelson, Daniel L. Gillen
Bayesian Evaluation Of Group Sequential Clinical Trial Designs, Scott S. Emerson, John M. Kittelson, Daniel L. Gillen
UW Biostatistics Working Paper Series
Clincal trial designs often incorporate a sequential stopping rule to serve as a guide in the early termination of a study. When choosing a particular stopping rule, it is most common to examine frequentist operating characteristics such as type I error, statistical power, and precision of confi- dence intervals (Emerson, et al. [1]). Increasingly, however, clinical trials are designed and analyzed in the Bayesian paradigm. In this paper we describe how the Bayesian operating characteristics of a particular stopping rule might be evaluated and communicated to the scientific community. In particular, we consider a choice of probability models and a …
On The Use Of Stochastic Curtailment In Group Sequential Clinical Trials, Scott S. Emerson, John M. Kittelson, Daniel L. Gillen
On The Use Of Stochastic Curtailment In Group Sequential Clinical Trials, Scott S. Emerson, John M. Kittelson, Daniel L. Gillen
UW Biostatistics Working Paper Series
Many different criteria have been proposed for the selection of a stopping rule for group sequen- tial trials. These include both scientific (e.g., estimates of treatment effect) and statistical (e.g., frequentist type I error, Bayesian posterior probabilities, stochastic curtailment) measures of the evidence for or against beneficial treatment effects. Because a stopping rule based on one of those criteria induces a stopping rule on all other criteria, the utility of any particular scale relates to the ease with which it allows a clinical trialist to search for sequential sampling plans having de- sirable operating characteristics. In this paper we examine …