ASA Connect

 View Only

Call for abstracts: Measurement Error in Longitudinal Data Workshop

  • 1.  Call for abstracts: Measurement Error in Longitudinal Data Workshop

    Posted 12-05-2018 04:22
    Call for abstracts
    Measurement Error in Longitudinal Data Workshop
    Manchester, UK
    19-21 June 2019

     

    It is our great pleasure to invite you to the Measurement Error in Longitudinal Data workshop. This workshop aims to bring together the latest developments in estimating and correcting for measurement error in longitudinal data. We are aiming for an interdisciplinary meeting and encourage colleagues from across a range of disciplines to submit an abstract. We especially encourage submissions from: survey research, statistics, psychology, education, health, economics, marketing, and data science. Abstracts should emphasize a measurement error topic relevant to longitudinal data. Possible topics may include (but are not limited to):

    -          Design of longitudinal data collection to minimize measurement error

    -          Estimating measurement error using experimental designs

    -          Statistical models for estimating measurement error

    -          Ways of correct for measurement error post-survey data collection

    -          Impact of measurement error on substantive research and policy making

    -          The use of adaptive designs to minimize measurement error

    -          Measurement error in different settings (e.g., admin data, social media data, biological data)

    -          Measurement error in online panel surveys

    An edited book is being planned as part of the workshop. If you are interested in contributing a chapter to the book, please indicate your interest in the abstract submission form. 

    Please submit an abstract by the 20th of January 2019 using the link below:

    https://goo.gl/forms/ShNkF60lPfLq7LVl1

    Notifications of acceptance will be sent to authors by the 1st of February 2019.

    Registration to the workshop is free thanks to support from the National Centre for Research Methods, Methods@Manchester and the Survey Methods Research Group at the University of Manchester.

     

    Alexandru Cernat, University of Manchester, UK

    Joseph Sakshaug, Institute for Employment Research (IAB) and University of Mannheim, Germany