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  • 1.  Looking for assistance with Small Area Estimation

    Posted 12-05-2019 19:34
    Friends,

    Hello my name is Mike.   Currently,  I am working on an project using the small area estimation.   I am looking for some easy to read material to help me understand how this statistical method works, what parameters I need to set for my model, and best practices using small area estimation. 

    I would like to invite anyone who would like to share information with me to help me complete my project to reply to this email or message me directly at my email datamike8@gmail.com. 

    Thanks,

    Mike

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    Michael Jadoo

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  • 2.  RE: Looking for assistance with Small Area Estimation

    Posted 12-06-2019 13:41
    Small area estimate approaches are diverse. There are three main methods:

    1. Multilevel regression: 
    Reference: Zhang, X, Holt, J B, Lu, H, Wheaton, A G, Ford, E S, Greenlund, K J and Croft, J B 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. Am J Epidemiol 179: 1025–1033. DOI: https://doi.org/10.1093/aje/kwu018

    2. Space-time logistic regression:
    Dwyer-Lindgren, L, Flaxman, A D, Ng, M, Hansen, G M, Murray, C J and Mokdad, A H 2015 Drinking Patterns in US Counties From 2002 to 2012. Am J Public Health 105: 1120–1127. DOI: https://doi.org/10.2105/AJPH.2014.302313

    3. Bayesian Poisson model:
    Cadwell, B L, Thompson, T J, Boyle, J P and Barker, L E 2010 Bayesian small area estimates of diabetes prevalence by US county, 2005. J Data Sci 8: 173–188.

    There is no easy to read material. Here is a comparison of the three methods published by myself, which may help you have a quick sense about the differences of the three methods in methodology and data analysis:
    Chien, L-C, Lin, G., Li, X., Zhang X. (2018) Disparity of Imputed Data from Small Area Estimate Approaches – A Case Study on Diabetes Prevalence at The County Level in the U.S. Data Science Journal. 17: p8.

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    Lung-Chang Chien
    Assistant Professor
    Epidemiology and Biostatistics Program
    Department of Environmental and Occupational Health
    School of Public Health
    University of Nevada, Las Vegas
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    Original Message


  • 3.  RE: Looking for assistance with Small Area Estimation

    Posted 12-09-2019 10:48
    Hello,

    I refer you to the following Small Area Estimation book authored by J.N.K. Rao and I. Molina (2015) and references therein.

    Rao, J.N.K. and Molina, I.(2015), Small Area Estimation, 2nded., Wiley, New York.


    Mahmoud
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-~~
    Mahmoud Torabi, PhD
    Associate Professor of Biostatistics, Department of Community Health Sciences
    Adjunct Professor, Department of Statistics
    Scientist, Children's Hospital Research Institute of Manitoba (CHRIM)
    Past-President, Survey Methods Section, Statistical Society of Canada

    University of Manitoba,
    Winnipeg, MB, R3E 0W3 Canada
    Tel:  (204) 272-3136
    Fax: (204) 789-3905
    E-mail: Mahmoud.Torabi@umanitoba.ca
    Web: http://home.cc.umanitoba.ca/~torabi
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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    Mahmoud Torabi
    Associate Professor of Biostatistics
    University of Manitoba
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    Original Message


  • 4.  RE: Looking for assistance with Small Area Estimation

    Posted 12-09-2019 11:05
    Perhaps you should start reading the second edition of my book: J. N. K. Rao and Isabel Molina, Small Area Estimation, Wiley 2015. This book gives a comprehensive account of small area estimation methods currently available including those used in producing official statistics. The book also gives illustrations using R program developed by Isabel Molina.

    Another good reference, especially for official statistics, is the paper "From start to finish: a framework for the production of small area official statistics, Journal of the Royal Statistical Society, series A, 2018, vol. 181, 927-979. This paper covers basic methods and provides clear guidelines with illustrations.

     J. N. K. Rao
    Distinguished Research Professor
    Carleton University
    Ottawa, Canada

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    J. Rao
    Carleton University
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    Original Message


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