An Unbiased Estimator of the Variance of Simple Random Sampling Using Mixed Random-Systematic Sampling
Systematic sampling is a commonly used technique due to its simplicity and ease of implementation. The drawback of this simplicity is that it is not possible to estimate the design variance without bias. There are several ways to circumvent this problem. One method is to suppose that the variable of interest has a random order in the population, so the sample variance of simple random sampling without replacement is used. By means of a mixed random - systematic sample, an unbiased estimator of the population variance for simple random sample is proposed without model assumptions. Some examples are given.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kuo-Chung Huang, 2004. "Mixed random systematic sampling designs," Metrika, Springer, vol. 59(1), pages 1-11, 02.
When requesting a correction, please mention this item's handle: RePEc:bdm:wpaper:2009-13. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dirección de Sistemas)
If references are entirely missing, you can add them using this form.