| 036a | XA-GB |
| 037b | eng |
| 077a | 1748448382 Erscheint auch als (Druck-Ausgabe): ‡Measurement error in longitudinal data |
| 087q | 978-0-19-885998-7 |
| 100b | Cernat, Alexandru ¬[HerausgeberIn]¬ |
| 104b | Sakshaug, Joseph W. ¬[HerausgeberIn]¬ |
| 331 | Measurement error in longitudinal data |
| 410 | Oxford |
| 412 | Oxford University Press |
| 425 | 2021 |
| 425a | 2021 |
| 433 | 1 Online-Ressource : Illustrationen |
| 451b | Oxford scholarship online |
| 501 | This edition also issued in print: 2021 |
| 501 | Includes bibliographical references and index |
| 527 | Erscheint auch als (Druck-Ausgabe): ‡Measurement error in longitudinal data |
| 540a | ISBN 978-0-19-189244-8 ebook : (No price) |
| 700 | |62-06 |
| 700 | |00B15 |
| 700 | |62M30 |
| 700 | |62D20 |
| 700b | |519.53 |
| 700g | 1271481863 SK 840 |
| 750 | Longitudinal data is essential for understanding how the world around us changes. Most theories in the social sciences and elsewhere have a focus on change, be it of individuals, of countries, of organisations, or of systems, and this is reflected in the myriad of longitudinal data that are being collected using large panel surveys. This type of data collection has been made easier in the age of Big Data and with the rise of social media. Yet our measurements of the world are often imperfect, and longitudinal data is vulnerable to measurement errors which can lead to flawed and misleading conclusions. This book tackles the important issue of how to investigate change in the context of imperfect data. |
| 902s | 209642505 Messfehler |
| 902s | 208908633 Empirische Sozialforschung |
| 902s | 209948361 Panelanalyse |
| 902s | 211538906 Hidden-Markov-Modell |
| 902s | 210961228 Tendenz |
| 902s | 208915567 Faktorenanalyse |
| 902s | 210215690 Reliabilität |
| 012 | 1755738749 |
| 081 | Measurement error in longitudinal data |
| 100 | E-Book Oxford EBS |
| 125a | Elektronischer Volltext - Campuslizenz |
| 655e | $uhttps://dx.doi.org/10.1093/oso/9780198859987.001.0001 |
