Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Miech on 'generational forgetting' about drug-use dangers

Impacts of H-1B visas: Lower prices and higher production - or lower wages and higher profits?

MTF data show 10% of 19-20 year-olds report bouts of drinking 10-plus alcoholic beverages

More News


Call for papers: Conference on computational social science, April 2017, U-M

Sioban Harlow honored with 2017 Sarah Goddard Power Award for commitment to women's health

Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

ICPSR Summer Program scholarships to support training in statistics, quantitative methods, research design, and data analysis

More Highlights

Next Brown Bag

Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

Michael R. Elliott photo

A Simple Method to Generate Equal-Sized Homogenous Strata or Clusters for Population-Based Sampling

Publication Abstract

Elliott, Michael R. 2011. "A Simple Method to Generate Equal-Sized Homogenous Strata or Clusters for Population-Based Sampling." Annals of Epidemiology, 21(4): 290-296.

PURPOSE: Statistical efficiency and cost efficiency can be achieved in population-based samples through stratification and/or clustering. Strata typically combine subgroups of the population that are similar with respect to an outcome. Clusters are often taken from preexisting units, but may be formed to minimize between-cluster variance, or to equalize exposure to a treatment or risk factor. Area probability sample design procedures for the National Children's Study required contiguous strata and clusters that maximized within-stratum and within-cluster homogeneity while maintaining approximately equal size of the strata or clusters. However, there were few methods that allowed such strata or clusters to be constructed under these contiguity and equal size constraints. METHODS: A search algorithm generates equal-size cluster sets that approximately span the space of all possible clusters of equal size. An optimal cluster set is chosen based on analysis of variance and convexity criteria. RESULTS: The proposed algorithm is used to construct 10 strata based on demographics and air pollution measures in Kent County, MI, following census tract boundaries. A brief simulation study is also conducted. CONCLUSIONS: The proposed algorithm is effective at uncovering underlying clusters from noisy data. It can be used in multi-stage sampling where equal-size strata or clusters are desired. Ann Epidemiol 2011;21:290-296. (C) 2011 Elsevier Inc. All rights reserved.

DOI:10.1016/j.annepidem.2010.11.016 (Full Text)

PMCID: PMC3073640. (Pub Med Central)

Country of focus: United States of America.

Browse | Search : All Pubs | Next