IDEAS home Printed from https://ideas.repec.org/a/spr/astaws/v9y2015i2p131-157.html
   My bibliography  Save this article

Sampling and Weighting Cohort Samples in Institutional Contexts

Author

Listed:
  • Hans Walter Steinhauer
  • Christian Aßmann
  • Sabine Zinn
  • Solange Goßmann
  • Susanne Rässler

Abstract

Das Nationale Bildungspanel erhebt unter anderem Kohortenstichproben von Kindergartenkindern, Schülern in der Klasse 5 und Schülern in der Klasse 9. Dieser Beitrag beschreibt detailliert die Stichprobenpläne dieser Kohorten. Die eingesetzten Stichprobenverfahren umfassen dabei indirekte Stichprobenziehung, Schichtung und zweistufige Klumpenstichproben. Im Rahmen der Erstellung der Gewichte werden im ersten Schritt Designgewichte hergeleitet. Im zweiten Schritt werden diese adjustiert, um für Teilnahmeverweigerungen innerhalb der Bruttostichprobe zu kompensieren. Diese Anpassungen kommen sowohl bei der Teilnahmeverweigerung auf institutioneller als auch auf individueller Ebene zur Anwendung. Die Klumpung von Individuen in Institutionen wird durch Zufallseffekte in den Regressionen berücksichtigt. Die empirischen Ergebnisse zeigen, dass die Teilnahme von Kindergartenkindern signifikant dadurch beeinflusst wird, ob das Kind mit beiden Eltern oder nur mit einem Elternteil zusammenlebt. Bei Schülern hingegen wird die Teilnahmebereitschaft durch die zu Hause gesprochene Sprache (Deutsch oder eine andere Sprache), sowie Kompetenzen in Mathematik und Deutsch maßgeblich beeinflusst. Abschließend werden Möglichkeiten zur Bereitstellung von Quer- und Längsschnittgewichten für Folgewellen der Panelerhebungen dargestellt. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Hans Walter Steinhauer & Christian Aßmann & Sabine Zinn & Solange Goßmann & Susanne Rässler, 2015. "Sampling and Weighting Cohort Samples in Institutional Contexts," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 9(2), pages 131-157, November.
  • Handle: RePEc:spr:astaws:v:9:y:2015:i:2:p:131-157
    DOI: 10.1007/s11943-015-0162-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11943-015-0162-0
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11943-015-0162-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Skinner, Chris J. & D'Arrigo, Julia, 2011. "Inverse probability weighting for clustered nonresponse," LSE Research Online Documents on Economics 40308, London School of Economics and Political Science, LSE Library.
    2. C. J. Skinner & D'arrigo, 2011. "Inverse probability weighting for clustered nonresponse," Biometrika, Biometrika Trust, vol. 98(4), pages 953-966.
    3. Lynn, Peter & Kaminska, Olena, 2010. "Weighting strategy for Understanding Society," Understanding Society Working Paper Series 2010-05, Understanding Society at the Institute for Social and Economic 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. Ralf Thomas Münnich, 2015. "Vorwort des Herausgebers," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 9(2), pages 79-81, November.
    2. Sabine Zinn & Ariane Würbach & Hans Walter Steinhauer & Angelina Hammon, 2020. "Attrition and selectivity of the NEPS starting cohorts: an overview of the past 8 years [Ausfall und Selektivitäten in den NEPS Startkohorten: ein Überblick über die letzten 8 Jahre]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 14(2), pages 163-206, July.
    3. Ann-Kristin Kreutzmann, 2018. "Estimation of sample quantiles: challenges and issues in the context of income and wealth distributions [Die Schätzung von Quantilen: Herausforderungen und Probleme im Kontext von Einkommens- und V," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 245-270, December.
    4. Hans Kiesl, 2016. "Indirect Sampling: A Review of Theory and Recent Applications," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(4), pages 289-303, December.
    5. Carol, Sarah & Schulz, Benjamin, 2018. "Religiosity as a bridge or barrier to immigrant children’s educational achievement?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 55, pages 75-88.

    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. Jouni Kuha & Myrsini Katsikatsou & Irini Moustaki, 2018. "Latent variable modelling with non‐ignorable item non‐response: multigroup response propensity models for cross‐national analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1169-1192, October.
    2. Youjin Lee & Trang Q. Nguyen & Elizabeth A. Stuart, 2021. "Partially pooled propensity score models for average treatment effect estimation with multilevel data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1578-1598, October.
    3. Plewis Ian & Shlomo Natalie, 2017. "Using Response Propensity Models to Improve the Quality of Response Data in Longitudinal Studies," Journal of Official Statistics, Sciendo, vol. 33(3), pages 753-779, September.
    4. Helene Boistard & Guillaume Chauvet & David Haziza, 2016. "Doubly Robust Inference for the Distribution Function in the Presence of Missing Survey Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 683-699, September.
    5. Brick J. Michael, 2013. "Unit Nonresponse and Weighting Adjustments: A Critical Review," Journal of Official Statistics, Sciendo, vol. 29(3), pages 329-353, June.
    6. Li He & Yu-Bo Wang & William C. Bridges & Zhulin He & S. Megan Che, 2023. "Bayesian Framework for Causal Inference with Principal Stratification and Clusters," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 114-140, April.
    7. Crossley, Thomas F. & Fisher, Paul & Low, Hamish, 2021. "The heterogeneous and regressive consequences of COVID-19: Evidence from high quality panel data," Journal of Public Economics, Elsevier, vol. 193(C).
    8. Michaela Benzeval & Jon Burton & Thomas Crossley & Paul Fisher & Annette Jäckle & Hamish Low & Brendan Read, 2020. "The idiosyncratic impact of an aggregate shock: the distributional consequences of COVID-19," IFS Working Papers W20/15, Institute for Fiscal Studies.
    9. Wolfram, Tobias, 2023. "(Not just) Intelligence stratifies the occupational hierarchy: Ranking 360 professions by IQ and non-cognitive traits," Intelligence, Elsevier, vol. 98(C).
    10. Koltsova Anna A. & Starobinskaya Nadegda M. & Chekmarev Oleg P., 2018. "Art Market: Distinctive Features And Value Of Art Objects," Annals of marketing-mba, Department of Marketing, Marketing MBA (RSconsult), vol. 4, December.
    11. Whitley, Elise & McCartney, Gerard & Bartley, Mel & Benzeval, Michaela, 2022. "Examining the impact of different social class mechanisms on health inequalities: A cross-sectional analysis of an all-age UK household panel study," Social Science & Medicine, Elsevier, vol. 312(C).

    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:spr:astaws:v:9:y:2015:i:2:p:131-157. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.