Last modified: 2018-05-31
Abstract
Pure crowdsourcing is in contrast with formal sample design. Indeed, in the latter, the choice of units is suggested by a precise mechanism which allows the calculation of the probability of inclusion while crowdsourced data units are self-selected and no probabilities of inclusion can be calculated. In our method, by exploiting the location of the collectors, the map of the crowdsourced data-points is compared with the map of points selected according to a formal spatial design with equivalent sample size. The observations are then reweighted so as to resemble the optimal plan. In this paper, we considered, in particular, the Local Pivotal Method 2 (Grafström, 2012) and we report some results of application of the suggested method to price data recently crowdsourced by FAO in 16 local markets of Kaduna State (Nigeria).
Â
References
Grafström A, Lundström NL, Schelin L. (2012) Spatially balanced sampling through the pivotal method, Biometrics, 68(2):514-20.