On triple sampling scremes for estimating from binomial data with misclassification errors^∗

^∗This paper was presented at the International Meeting on Analysis of Sample Survey Data and Sequential Analysis at Hebrew University, Jerusalem, Israel on June 14, 2982.

Abstract

Previous work has been carried out on the use of double sampling schemes for inference from binomial data which are subject to misclassification. The double sampling scheme utilizes a sample of n units which are classified by both a fallible and a true device and another sample of n₂ units which are classified only by a fallible device. A triple sampljng scheme incorporates an additional sample of n_l units which are classified only by the true device. In this paper we apply this triple sampling to estimation from binomialdata. First estimation of a binomial proportion is discussed under different misclassification structures. Then, the problem of optimal allocation of sample sizes is discussed.

Keywords:

• Double sampling
• maximum likelihood estimation
• sample size determination

^∗This paper was presented at the International Meeting on Analysis of Sample Survey Data and Sequential Analysis at Hebrew University, Jerusalem, Israel on June 14, 2982.

^∗This paper was presented at the International Meeting on Analysis of Sample Survey Data and Sequential Analysis at Hebrew University, Jerusalem, Israel on June 14, 2982.

Notes

^∗This paper was presented at the International Meeting on Analysis of Sample Survey Data and Sequential Analysis at Hebrew University, Jerusalem, Israel on June 14, 2982.