Estimating a binomial proportion from several independent samples

Qiao, C. G.; Wood, Graham R.; Lai, C. D.

doi:10.1080/01140671.2005.9514362

Cited by 5 publications

(7 citation statements)

References 9 publications

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“…Some typical plots (Figures 2.1(a)-2.1(c)) are drawn using this density function, with varying coefficient of variation (CV) for the denominator variable. From the considerations of Section 2 and Qiao et al [14], it is evident that the CV of the denominator is of critical importance. In Figure 2.1(a), the CV of both X and Y is small (0.1).…”

Section: The Probability Density Function Of the Ratio Of Independentmentioning

confidence: 95%

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Comparison of two common estimators of the ratio of the means of independent normal variables in agricultural research

Qiao¹,

Wood

Lai

et al. 2006

Journal of Applied Mathematics and Decision Sciences

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This paper addresses the problem of estimating the ratio of the means of independent normal variables in agricultural research. The first part of the research examines the distributional properties of the ratio of independent normal variables, both theoretically and using simulation. The second part of the research evaluates the relative merits of two common estimators of the ratio of the means of independent normal variables in agricultural research, an arithmetic average and a weighted average, via simulation experiments using normal distributions. The results are then tested using research data from rice breeding multi-environment trials in Jilin Province, China, in 1994. These data are used to demonstrate the diagnostic approach developed for assessing the “safe” use of the arithmetic and the weighted average methods for estimating the ratio of the means of independent normal variables.

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Section: The Probability Density Function Of the Ratio Of Independentmentioning

confidence: 95%

“…We have not, however, found any report in the literature comparing these two methods. We note that related research was conducted in Qiao et al [14], where the corresponding estimators of a binomial proportion using several independent samples in agricultural research were investigated. That work provided the impetus for the current study.…”

Section: Introductionmentioning

confidence: 99%

Comparison of two common estimators of the ratio of the means of independent normal variables in agricultural research

Qiao¹,

Wood

Lai

et al. 2006

Journal of Applied Mathematics and Decision Sciences

Self Cite

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“…Proportions (e.g. germination percentage) were estimated by weightaveraging proportionally to the number of seeds in each well 39 . By considering that the number of seeds in each well is an independent random variable, such a method is more appropriate than the arithmetic average for binomial distributions comparisons.…”

Section: Statistical Analysesmentioning

confidence: 99%

ScreenSeed as a novel high throughput seed germination phenotyping method

Merieux¹,

Cordier²,

Wagner³

et al. 2021

Sci Rep

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A high throughput phenotyping tool for seed germination, the ScreenSeed technology, was developed with the aim of screening genotype responsiveness and chemical drugs. This technology was presently used with Arabidopsis thaliana seeds to allow characterizing seed samples germination behavior by incubating seeds in 96-well microplates under defined conditions and detecting radicle protrusion through the seed coat by automated image analysis. This study shows that this technology provides a fast procedure allowing to handle thousands of seeds without compromising repeatability or accuracy of the germination measurements. Potential biases of the experimental protocol were assessed through statistical analyses of germination kinetics. Comparison of the ScreenSeed procedure with commonly used germination tests based upon visual scoring displayed very similar germination kinetics.

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“…The study is motivated from problems on pooling proportion from a binomial model detailed in medical or epidemiological literature. Six datasets (numbered D I to D VI) are extracted from four such studies that provide meta analysis, clinical trial, and statistical genetics data; D I and D II from [34], D III and D IV from [50], D V and D VI are respectively from [27] and [33]. All these studies have focused on approaches for combining proportions.…”

Section: Examplesmentioning

confidence: 99%

A Comparative Study on Methods for Measuring Heterogeneity in Binomial Proportion – Meta Analytic Approach

Sakthivel¹,

Subbiah²,

Ramakrishnan³

2018

IJCTS

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Statistical inference on a common quantity of interest arising from multiple related studies is quite pervasive in medical, social, statistical genetics, clinical trials, and epidemiological research. However, a scope is identified to study the issues related to pooling proportion across many Bernoulli type of events. The Main objective of the study is to exploit the asymptotic approximation of proportion and logit transformation in random effects model. Seven procedures for estimating between-variance in frequentist inferential methods have been used. Number of Bernoulli trials, number of studies, and events occurred at boundaries of the parameter are prime data characteristics considered in the study. From the results it is possible to device a methodology to choose more appropriate methods under different problem situations. All the procedures are implemented in R and major functions are presented in Appendix.

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Estimating a binomial proportion from several independent samples

Cited by 5 publications

References 9 publications

Comparison of two common estimators of the ratio of the means of independent normal variables in agricultural research

Comparison of two common estimators of the ratio of the means of independent normal variables in agricultural research

ScreenSeed as a novel high throughput seed germination phenotyping method

A Comparative Study on Methods for Measuring Heterogeneity in Binomial Proportion – Meta Analytic Approach

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