Showing papers on "Population proportion published in 2002"
01 Jan 2002
TL;DR: Inverse sampling and formal sequential designs may prove useful in reducing the sample size in studies where a small population proportion p is compared with a hypothesized reference proportion p 0 as mentioned in this paper, and the expected savings in sample size, when the alternative hypothesis is true, are 20% of the fixed sample size for the inverse sampling design and 40% for the triangular sequential design.
Abstract: Inverse sampling and formal sequential designs may prove useful in reducing the sample size in studies where a small population proportion p is compared with a hypothesized reference proportion p0. These methods are applied to the design of a cytogenetic study about chromosomal abnormalities in men with a daughter affected by Turner's syndrome. First it is shown how the calculated sample size for a classical design depends on the parameterization used. Later this sample size is compared with the required sample size in an inverse sampling design and a triangular sequential design using four different parameterizations (absolute differences, log-odds ratio, angular transform and Sprott's transform). The expected savings in sample size, when the alternative hypothesis is true, are 20% of the fixed sample size for the inverse sampling design and 40% for the triangular sequential design
3 citations
TL;DR: In this paper, the authors explore the overlap between two associated confidence intervals and conclude that, among three methods, the overlapped method is under-estimated, and the difference of the population proportions method is overestimated on the basis of the proposed method.
Abstract: In order to examine whether the difference between two point estimates of population proportions is statistically significant, data analysts use two techniques. The first is to explore the overlap between two associated confidence intervals. Second method is to test the significance which is introduced at most statistical textbooks under the common assumptions of consistency, asymptotic normality, and asymptotic independence of the estimates. Under the null hypothesis which is two population proportions are equal, the pooled estimator (If population proportion is preferred as a point estimator since two independent random samples are considered to be collected from one population. Hence as an alternative method, we could obtain another confidence interval of the difference of the population proportions with using the pooled estimate. We conclude that, among three methods, the overlapped method is under-estimated, and the difference of the population proportions method is over-estimated on the basis of the proposed method.