Ricerc@Sapienza

Resampling methods are widely studied and increasingly employed in applied
research and practice. When dealing with complex sampling designs, common
resampling techniques require to adjust non-integer sampling weights in order to
construct the so called “pseudo-population” where to perform the actual resampling.
In particular, to lighten the computational burden, it is commonly suggested
to round resampling weights to the nearest integer. This practice, however, has
been empirically shown to be harmful under general designs. Here we develop
theoretical support for this fact, and present asymptotic results concerning the bias
induced by the rounding practice.