A generalization of the Lavallée and Hidiroglou algorithm for stratification in business Surveys

This paper suggests stratification algorithms that account for a discrepancy between the stratification variable and the study variable when planning a stratified survey design. Two models are proposed for the change between these two variables. One is a log-linear regression model; the other postulates that the study variable and the stratification variable coincide for most units, and that large discrepancies occur for some units. Then, the Lavallée and Hidiroglou (1988) stratification algorithm is modified to incorporate these models in the determination of the optimal sample sizes and of the optimal stratum boundaries for a stratified sampling design. An example illustrates the performance of the new stratification algorithm. A discussion of the numerical implementation of this algorithm is also presented.