Multi-way stratification by linear programming - ARCHIVED

Rao and Nigam (1990, 1992) showed how a class of controlled sampling designs can be implemented using linear programming. In this article their approach is applied to multi-way stratification. A comparison is made with existing methods both by illustrating the sampling schemes generated for specific examples and by evaluating mean squared errors. The proposed approach is relatively simple to use and appears to have reasonable mean squared error properties. The computations required can, however, increase rapidly as the number of cells in the multi-way classification increase. Variance estimation is also considered.