Statistical matching attempts to combine the information obtained from different non-overlapping samples. The samples selected are often non representative of the finite population from which they are taken and not all the sampled units respond. The aim of this paper is to illustrate how informative sampling and not missing at random (NMAR) nonresponse can be handled in the statistical matching context.
A parametric empirical likelihood approach to data matching under nonignorable sampling and nonresponse / Marella, D.; Pfeffermann, D.. - (2021). (Intervento presentato al convegno 50th edition of the Scientific Meeting of the Italian Statistical Society tenutosi a online).
A parametric empirical likelihood approach to data matching under nonignorable sampling and nonresponse
Marella D.;
2021
Abstract
Statistical matching attempts to combine the information obtained from different non-overlapping samples. The samples selected are often non representative of the finite population from which they are taken and not all the sampled units respond. The aim of this paper is to illustrate how informative sampling and not missing at random (NMAR) nonresponse can be handled in the statistical matching context.| File | Dimensione | Formato | |
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