이중표본에서 모비율의 구간추정

Lee, Seung-Chun;Choi, Byong-Su
이승천;최병수

• Accepted : 20091000
• Published : 2009.12.31
• 68 12

Abstract

The double sampling scheme is effective in reducing the sampling cost. However, the doubly sampled data is contaminated by two types of error, namely false-positive and false-negative errors. These would make the statistical analysis more difficult, and it would require more sophisticate analysis tools. For instance, the Wald method for the interval estimation of a proportion would not work well. In fact, it is well known that the Wald confidence interval behaves very poorly in many sampling schemes. In this note, the property of the Wald interval is investigated in terms of the coverage probability and the expected width. An alternative confidence interval based on the Agresti-Coull's approach is recommended.

Keywords

False-positive error;false-negative error;Wald confidence interval;Agresti-Coull confidence interval;coverage probability

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Cited by

1. Theoretical Considerations for the Agresti-Coull Type Confidence Interval in Misclassified Binary Data vol.18, pp.4, 2011, https://doi.org/10.5351/CKSS.2011.18.4.445
2. Bayesian confidence intervals of proportion with misclassified binary data vol.42, pp.3, 2013, https://doi.org/10.1016/j.jkss.2012.09.001

Acknowledgement

Supported by : 한국학술진흥재단