원문정보
초록
영어
Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term. In some cases, the measurement error variance may be also a function of the unknown true value. The error variance function can be rewritten as a function of true value multiplied by a scale factor. This research explore methods for estimation of the measurement error variance based on the data from complex sampling design. We consider the case in which the variance of mesurement error is a linear function of unknown true value, and the error variance scale factor is small. We applied our results to the U.S. Third National Health and Nutrition Examination Survey (the U.S. NHANES Ⅲ) data for empirical analyses, which has replicate measurements for relatively small subset of initial respondents's group.
목차
1. Introduction
2. Experimental
2.1 Measurement Error Models
2.2 Linear Measurement Error Variance Function
2.3 Design Based Estimation of Measurement Error Variance
2.4 Propensity Model
3. Results and Discussion
4. Conclusion
References