Titolo Methods for variance estimation under random hot deck imputation in business surveys Periodico Rivista di statistica ufficiale Anno: 2014 - Fascicolo: 1/2 - Pagina iniziale: 45 - Pagina finale: 64
When imputed values are treated as if they were observed, the precision of the estimates is
generally overstated. In the paper three variance methods under imputation are taken into
account. Two of them are the wellknown bootstrap and Multiple Imputation. The third is
a new method based on grouped jackknife easy to implement, not computer intensive and
suitable when random hot deck imputation is performed. A simulative comparison on real
business data has been carried out. The findings show that the proposed method has good performances with respect to the other two.