Measurement Invariance

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Tác giả: Alain De Beuckelaer, Peter Schmidt, Rens Van De Schoot

Ngôn ngữ: eng

ISBN-13: 978-2889196500

Ký hiệu phân loại:

Thông tin xuất bản: Frontiers Media SA, 2015

Mô tả vật lý: 1 electronic resource (217 p.)

Bộ sưu tập: Tài liệu truy cập mở

ID: 203886

 Multi-item surveys are frequently used to study scores on latent factors, like human values, attitudes and behavior. Such studies often include a comparison, between specific groups of individuals, either at one or multiple points in time. If such latent factor means are to be meaningfully compared, the measurement structures including the latent factor and their survey items should be stable across groups and/or over time, that is 'invariant'. Recent developments in statistics have provided new analytical tools for assessing measurement invariance (MI). The aim of this special issue is to provide a forum for a discussion of MI, covering some crucial 'themes': (1) ways to assess and deal with measurement non-invariance
  (2) Bayesian and IRT methods employing the concept of approximate measurement invariance
  and (3) new or adjusted approaches for testing MI to fit increasingly complex statistical models and specific characteristics of survey data. The special issue started with a kick-off meeting where all potential contributors shared ideas on potential papers. This expert workshop was organized at Utrecht University in The Netherlands and was funded by the Netherlands Organization for Scientific Research (NWO-VENI-451-11-008). After the kick-off meeting the authors submitted their papers, all of which were reviewed by experts in the field. The papers in the eBook are listed in alphabetical order, but in the editorial the papers are introduced thematically. Although it is impossible to cover all areas of relevant research in the field of MI, papers in this eBook provide insight on important aspects of measurement invariance. We hope that the discussions included in this special issue will stimulate further research on MI and facilitate further discussions to support the understanding of the role of MI in multi-item surveys.
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