Researchers investigated 2 major sources of nonsampling errors—nonresponse and noncoverage—in fishing surveys. How do these sources of missing data affect the accuracy of survey estimates? Do both nonsampling errors equally influence the results? New research on this topic appears in Two Sources of Nonsampling Error in Fishing Surveys, which is a chapter in a new ebook: Recent Advances on Sampling Methods and Educational Statistics. Westat’s J. Michael Brick, PhD, is the lead author of this research.
Proxy analyses show that in these surveys noncoverage leads to large biases, whereas nonresponse bias is negligible by comparison. In addition, it was found that the magnitude of bias is not predicted by the rate of missing data caused by nonresponse or noncoverage.