Estimating a binomial proportion from several independent samples

C. G. Qiao*, G. R. Wood, C. D. Lai

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)


    This paper addresses the problem of estimating a binomial proportion from several independent samples in agricultural research, where the arithmetic average is widely used. The penalties of using a suboptimal estimator, the arithmetic estimator, relative to the preferred best estimator, the weighted average, are theoretically and empirically investigated, using numerical illustrations and simulation studies. Raw count data from a study of the proportion of inoculated transgenic hairy roots expressing resistance to cyst nematode in soybean (Glycine max) cultivars and a set of 10 examples of proportion estimation involving several independent samples are used for a practical evaluation of the findings. Results show that using the arithmetic average estimator can inflate variance and widen large sample confidence intervals of the estimates. The weighted average is recommended.

    Original languageEnglish
    Pages (from-to)293-302
    Number of pages10
    JournalNew Zealand Journal of Crop and Horticultural Science
    Issue number3
    Publication statusPublished - Sep 2005


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