1 Interval estimators for the population mean for skewed distributions with a small sample size SUMMARY In nite population sampling it has long been known that for small sample sizes, when sampling from a skewed population, the usual frequentist intervals for the population mean cover the true value less often than their stated frequency of coverage. Recently a noninformative Bayesian approach ...

BACKGROUND A ubiquitous issue in research is that of selecting a representative sample from the study population. While random sampling strategies are the gold standard, in practice, random sampling of participants is not always feasible nor necessarily the optimal choice. In our case, a selection must be made of 12 hospitals (out of 89 Dutch hospitals in total). With this selection of 12 hospi...

Chain sampling plan for Log Logistic distribution when the life-test is truncated at a prespecified time is discussed. The design parameters such as the minimum sample size and the acceptance number necessary to assure a specified mean life time are obtained by satisfying the producer’s and consumer’s risks at the specified quality levels, under the assumption that the termination time and the ...

BACKGROUND In this paper we propose the use of the within-subject coefficient of variation as an index of a measurement's reliability. For continuous variables and based on its maximum likelihood estimation we derive a variance-stabilizing transformation and discuss confidence interval construction within the framework of a one-way random effects model. We investigate sample size requirements f...

In the context of economic design, a two-stage model is proposed that utilizes continuously variable sampling intervals. Specifically, each successive sampling interval is determined by the extremity of the latest sample. Modeling the situation as a Markov chain, the hourly cost is developed for any arbitrary set of design parameters. This proposed approach is found to be more economically desi...

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Estimation is the process of determining a likely value for a population parameter (eg, the true population mean or proportion) based on a random sample. In practice, a sample is drawn from the target population, and sample statistics (eg, the sample mean or sample proportion) are used to generate estimates of the unknown parameter. The sample should be representative of the population, ideally...