IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/76991.html
   My bibliography  Save this paper

Introduction to the design and analysis of complex survey data

Author

Listed:
  • Skinner, Chris J.
  • Wakefield, Jon

Abstract

We give a brief overview of common sampling designs used in a survey setting, and introduce the principal inferential paradigms under which data from complex surveys may be analyzed. In particular, we distinguish between design-based, model-based and model-assisted approaches. Simple examples highlight the key differences between the approaches. We discuss the interplay between inferential approaches and targets of inference and the important issue of variance estimation.

Suggested Citation

  • Skinner, Chris J. & Wakefield, Jon, 2017. "Introduction to the design and analysis of complex survey data," LSE Research Online Documents on Economics 76991, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:76991
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/76991/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lilli Japec & Frauke Kreuter & Marcus Berg & Paul Biemer & Paul Decker & Cliff Lampe & Julia Lane & Cathy O’Neil & Abe Usher, "undated". "Big Data in Survey Research: AAPOR Task Force Report," Mathematica Policy Research Reports c57e7c039f6a4db982b26c6fe, Mathematica Policy Research.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tymon Sloczynski & S. Derya Uysal & Jeffrey M. Wooldridge & Derya Uysal, 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," CESifo Working Paper Series 9715, CESifo.
    2. Jonathan Wakefield & Taylor Okonek & Jon Pedersen, 2020. "Small Area Estimation for Disease Prevalence Mapping," International Statistical Review, International Statistical Institute, vol. 88(2), pages 398-418, August.
    3. Sloczynski, Tymon & Uysal, Derya & Wooldridge, Jeffrey M., 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," IZA Discussion Papers 15241, Institute of Labor Economics (IZA).
    4. Sloczynski, Tymon & Uysal, Derya & Wooldridge, Jeffrey M., 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," IZA Discussion Papers 15241, Institute of Labor Economics (IZA).
    5. Taekyoung Kim & Sang D Choi & Shuping Xiong, 2020. "Epidemiology of fall and its socioeconomic risk factors in community-dwelling Korean elderly," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-14, June.
    6. Daily, Shay M. & Dyer, Angela M. & Lilly, Christa L. & Sarkees, Emily A. & Bias, Thomas K., 2022. "Using adverse childhood experiences to explore the usefulness of community health needs assessments to monitor complex determinants of health at the local level," Evaluation and Program Planning, Elsevier, vol. 91(C).
    7. Martina Patone & Li‐Chun Zhang, 2021. "On Two Existing Approaches to Statistical Analysis of Social Media Data," International Statistical Review, International Statistical Institute, vol. 89(1), pages 54-71, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martina Patone & Li‐Chun Zhang, 2021. "On Two Existing Approaches to Statistical Analysis of Social Media Data," International Statistical Review, International Statistical Institute, vol. 89(1), pages 54-71, April.
    2. S. Rinken & S. Pasadas-del-Amo & M. Rueda & B. Cobo, 2021. "No magic bullet: estimating anti-immigrant sentiment and social desirability bias with the item-count technique," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(6), pages 2139-2159, December.
    3. Veronika Hecht & Nicole Litzel & Johannes Schäffler, 2019. "Unit nonresponse at the firm level: a cross-border analysis using the IAB-ReLOC data," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-18, December.
    4. Barbara Felderer & Jannis Kueck & Martin Spindler, 2021. "Big Data meets Causal Survey Research: Understanding Nonresponse in the Recruitment of a Mixed-mode Online Panel," Papers 2102.08994, arXiv.org.
    5. Antonio Arcos & Maria del Mar Rueda & Sara Pasadas-del-Amo, 2020. "Treating Nonresponse in Probability-Based Online Panels through Calibration: Empirical Evidence from a Survey of Political Decision-Making Procedures," Mathematics, MDPI, vol. 8(3), pages 1-16, March.
    6. Camilla Salvatore & Silvia Biffignandi & Annamaria Bianchi, 2021. "Social Media and Twitter Data Quality for New Social Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 601-630, August.

    More about this item

    Keywords

    Design-based inference; model-assisted inference; model-based inference; weights; variance estimation.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:76991. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.