Chapter 22 Small Area Estimation

22.1 Small area estimation (SAE)

Small area estimation (SAE) is an umbrella term to describe a number of approaches that provide “reliable small area statistics even when only very small samples are available for these areas.” (Pfeffermann 2002) The applications are often seen

Many of these approaches are based upon Bayesian hierarchical models (see Gómez-Rubio et al. as one example).

22.1.1 Theory and methods

Australian Bureau of Statistics, Methodology Advisory Committee (2009) Small Area Estimation with Simulated Samples from the Population Census, research paper.

BIAS Project.

Cadwell, Betsy L., Theodore J. Thompson, James P. Boyle and Lawrence E. Barker (2010) “Bayesian Small Area Estimates of Diabetes Prevalence by U.S. County, 2005”, Journal of Data Science, 8, 173-188.

Chen, C.X., T. Lumley and J. Wakefield (?) “The Use of Sampling Weights in Bayesian Hierarchical Models for Small Area Estimation”_, Technical Report no.583, Department of Statistics, University of Washington, Seattle.

Ghosh, M. and J. N. K. Rao (1994). “Small area estimation: An appraisal.” Statistical Science 9(1), 55–76.

Goldstein, H. and D. J. Spiegelhalter (1996). “League tables and their limitations: Statistical issues in comparisons of institutional performance (with discussion).” Journal of the Royal Statistical Society, Series A 159(3), 385–443.

Gómez-Rubio, V., N. Best, S. Richardson and P. Clarke (2007) Bayesian Statistics, Small Area Estimation and why no one is poor in Sweden, presentation to the Royal Statistical Society Conference, 2007-07-18.

Gómez-Rubio, V., N. Best, S. Richardson and G. Li (2010) “Bayesian Statistics for Small Area Estimationalternate source via ResearchGate

Hidiroglou, Michael (2007) “Small-Area Estimation: Theory and Practice”, Proceedings of the Joint Statistical Meetings: Section on Survey Research Methods

Holt, D. and Fernando A.S. Moura (1999) “Small area estimation using multilevel models”, Survey Methodology (cat. 12-001-X), Statistics Canada, Vol.25 No.1,, pp.73-80, June 2015.

Jiang, Jiming (2010) Large Sample Techniques for Statistics (Chapter 13, "Small-Area Estimation).

Kim, Jae-kwang, Seunghwan Park and Seo-young Kim (2015) “Small area estimation combining information from several sources”, Survey Methodology (cat. 12-001-X), Statistics Canada, Vol.41 No.1, June 2015.

Longford, Nicholas T. (2005) Missing Data and Small-Area Estimation: Modern Analytical Equipment for the Survey Statistician. Springer.

Longford, Nicholas T. (2006) “Sample size calculation for small-area estimation”, Survey Methodology (cat. 12-001-X), Statistics Canada, Vol. 32, No. 1, pp. 87-96.

Marton, Krisztina and Jennifer C. Karberg, Rapporteurs, The Future of Federal Household Surveys: Summary of a Workshop, The National Academies Press

Molina, Isabel, J.N.K. Rao and Gauri Sankar Datta (2015) “Small area estimation under a Fay-Herriot model with preliminary testing for the presence of random area effects”, Survey Methodology (cat. 12-001-X), Statistics Canada, Vol.41 No.1, June 2015.

Petrucci, Alessandra, Monica Pratesi, and Nicola Salvati (2005) “Geographic Information in Small Area Estimation: Small Area Models and Spatially Correlated Random Area Effects”, January 2005,

Pfeffermann, Danny (2002) “Small Area Estimation – New Developments and Directions” (Pfeffermann 2002)

Phadia, Eswar G. (2016) Prior Processes and Their Applications: Nonparametric Bayesian Estimation (2nd ed.), Springer.

Public Health Ontario (2018) Small Area Analysis: A primer for Public Health Units

Rahman, Azizur and Ann Harding (2017) Small Area Estimation and Microsimulation Modeling (CRC Press page)

Rao, J. N. K. (2003). Small Area Estimation. John Wiley & Sons, Inc., Hoboken, New Jersey.

Seliske, L., T. A. Norwood, J. R. McLaughlin, S. Wang, C. Palleschi and E. Holowaty (2016) “Estimating micro area behavioural risk factor prevalence from large population-based surveys: a full Bayesian approach”, BMC Public Health.

Song, Lin; Laina Mercer; Jon Wakefield; Amy Laurent; David Solet (2016) “Using Small-Area Estimation to Calculate the Prevalence of Smoking by Subcounty Geographic Areas in King County, Washington, Behavioral Risk Factor Surveillance System, 2009–2013”, Preventing Chronic Disease 2016; 13:150536

Sperling, Jonathan (2012) [“The Tyranny of Census Geography: Small-Area Data and Neighborhood Statistics”], Cityscape, 14(2), pp.219-223,

Whitworth, Adam (ed.) (2013) Evaluations and improvements in small area estimation methodologies

Wieczorek, Jerzy (2013) Small Area Estimation resources, at

Wieczorek, Jerzy (2015) Small Area Estimation 101: old materials posted, at

Zhang, Xingyou, James B. Holt, Hua Lu, Anne G. Wheaton, Earl S. Ford, Kurt J. Greenlund and Janet B. Croft (2014) “Multilevel Regression and Poststratification for Small-Area Estimation of Population Health Outcomes: A Case Study of Chronic Obstructive Pulmonary Disease Prevalence Using the Behavioral Risk Factor Surveillance System”, American Journal of Epidemiology, 179-8, pp.1025-1033.

Zhou, Qian and Yong You (2011) Hierarchical Bayes small area estimation under a spatial model with application to health survey data, Statistics Canada, Survey Methodology Series (12-001-X) Academic community

Mahmoud Torabi, University of Manitoba, Rady Faculty of Health Sciences.

Adam Whitworth

22.1.2 R

Arranged by package


Bivand, Roger S., Edzer Pebesma and Virgilio Gómez-Rubio (2013) Applied Spatial Data Analysis with R, 2nd edition. Springer

Gómez-Rubio, Virgilio (2016) Small Area Estimation with R, tutorial at the UseR 2016 Conference, Stanford University.

Andrés Gutiérrez, 2017-04-16, Small Area Estimation 101( {sae}


CRAN page: sae: Small Area Estimation


Molina, Isabel and Yolanda Marhuenda (2015) “sae: An R Package for Small Area Estimation”, The R Journal Vol. 7/1, June 2015 {sae2}


CRAN page: sae2: Small Area Estimation: Time-series Models




Pfeffermann, Danny. 2002. “Small Area Estimation: New Developments and Directions.” International Statistical Review / Revue Internationale de Statistique 70 (1): 125–43.