Using the Superpopulation Model for Imputations and Variance Computation in Survey Sampling
نویسنده
چکیده
INTRODUCTION For estimation of population characteristics (mainly totals, means, counts) in business statistics surveys, the Czech Statistical Office (CZSO) has been recently exploring a new approach, in which all data for units that are out of the sample are imputed based on predictions by regression, instead of estimating the population characteristics through weighting. The all-data imputation is based on the superpopulation model (i.e. Cassel et al., 1977, chapter 4). Compared to classical survey methodology (i.e. Hájek, 1960, 1981 or Cochran, 1977), the data are treated as realizations of an infinite population, some of which we know through the survey and some we want to estimate. Traditional methods, on the other hand, work with the population at hand. All data are treated as fixed constants and the randomness of estimates then comes in form of sample inclusion indicators. The Using the Superpopulation Model for Imputations and Variance Computation in Survey Sampling
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