Construction of Indirect Sampling Weights Through Data Integration

Music City Center 

This paper employs the data integration approach to construct a new set of weights for the indirect sampling survey. By leveraging with the reference probability sample, we recast the indirectly sampled units as the non-probability sample to compute inverse probability weights. Compared to the existing Generalized Weight Share method, the proposed data-integrated weights can be applied to estimations of median and quantiles. In an empirical application of estimating merchant cash acceptance, we assess the effectiveness of our proposed indirect sampling weights in terms of bias and variance.

TBD