Mining the New Oil for Official Statistics 1
Siu‐Ming Tam, Jaekwang Kim, Lyndon Ang, Han H. N. Pham · 2020
In this chapter, the authors extend the results of S. M. Tam and J. K. Kim to continuous variables, again without making any missing-at-random assumptions on the inclusion mechanism for the nonprobability sample. They also extend data integration methods to address measurement errors in the data source (henceforth denoted as B), the simple random sample (denoted by A), and nonresponse biases in A. The authors describe the methods Tam and Kim used, and show how the two data sources, B and A, can be combined to address undercoverage bias in B and improve the efficiency in estimating the population total of the target population using A. They discuss the estimation of the population total when measurement errors occur in data source B or in the probability sample A. The authors present simulation results to illustrate the methods, and discuss two applications of the methods in official statistics with certain limitations.