Survey Methodology
Using balanced sampling in creel surveys

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by Ibrahima Ousmane Ida, Louis-Paul Rivest, and Gaétan DaigleNote 1

  • Release date: December 20, 2018

Abstract

These last years, balanced sampling techniques have experienced a recrudescence of interest. They constrain the Horvitz Thompson estimators of the totals of auxiliary variables to be equal, at least approximately, to the corresponding true totals, to avoid the occurrence of bad samples. Several procedures are available to carry out balanced sampling; there is the cube method, see Deville and Tillé (2004), and an alternative, the rejective algorithm introduced by Hájek (1964). After a brief review of these sampling methods, motivated by the planning of an angler survey, we investigate using Monte Carlo simulations, the survey designs produced by these two sampling algorithms.

Key Words:      Balanced sampling; Creel surveys; Cube method; Multistage sampling; Rejective algorithm; Monte Carlo simulation.

Table of contents

How to cite

Ousmane Ida, I., Rivest, L.-P. and Daigle, G. (2018). Using balanced sampling in creel surveys. Survey Methodology, Statistics Canada, Catalogue No. 12-001-X, Vol. 44, No. 2. Paper available at https://www150.statcan.gc.ca/n1/pub/12-001-x/2018002/article/54954-eng.htm.

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