Sabine Zinn, Ariane Würbach, Hans Walter Steinhauer, Angelina Hammon
{"title":"Attrition and selectivity of the NEPS starting cohorts: an overview of the past 8 years","authors":"Sabine Zinn, Ariane Würbach, Hans Walter Steinhauer, Angelina Hammon","doi":"10.1007/s11943-020-00268-7","DOIUrl":"10.1007/s11943-020-00268-7","url":null,"abstract":"<div><p>This article documents the number of target persons participating in the panel surveys of the National Educational Panel Study (NEPS) as well as the number of respondents who temporarily dropout and of those leaving the panel (attrition). NEPS comprises panel surveys with six mutually exclusive starting cohorts covering the complete life span. Sample sizes, numbers of participants and temporary as well as final dropouts and participation rates are reported in detail for each wave and for subsamples, if applicable. Sample particularities, such as the conversion of temporary dropouts into final ones, are elaborated on. All figures presented are derived from the corresponding Scientific Use Files (SUFs) published by February 1, 2018. Selectivity due to attrition (i.e., final dropouts) is studied. For this purpose, we examine how attrition distorts the NEPS samples with respect to relevant design variables (such as stratification criteria) and panel member characteristics (like sex and birth year). In detail, we study the panel status of each panel member, that is being part of the panel or having dropped out finally, along all of the panel waves with respect to starting cohort and population specific characteristics. We conclude this article with some recommendations for dealing with the detected selection bias in statistical analyses.</p></div>","PeriodicalId":100134,"journal":{"name":"AStA Wirtschafts- und Sozialstatistisches Archiv","volume":"14 2","pages":"163 - 206"},"PeriodicalIF":0.0,"publicationDate":"2020-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s11943-020-00268-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50468129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interview mit Wolfgang Schmid","authors":"Walter Krämer","doi":"10.1007/s11943-019-00267-3","DOIUrl":"10.1007/s11943-019-00267-3","url":null,"abstract":"","PeriodicalId":100134,"journal":{"name":"AStA Wirtschafts- und Sozialstatistisches Archiv","volume":"14 1","pages":"103 - 111"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s11943-019-00267-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50517289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joachim Engel, Rolf Biehler, Daniel Frischemeier, Susanne Podworny, Achim Schiller, Laura Martignon
{"title":"Erratum to: Zivilstatistik: Konzept einer neuen Perspektive auf Data Literacy und Statistical Literacy","authors":"Joachim Engel, Rolf Biehler, Daniel Frischemeier, Susanne Podworny, Achim Schiller, Laura Martignon","doi":"10.1007/s11943-019-00266-4","DOIUrl":"10.1007/s11943-019-00266-4","url":null,"abstract":"","PeriodicalId":100134,"journal":{"name":"AStA Wirtschafts- und Sozialstatistisches Archiv","volume":"14 1","pages":"113 - 114"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s11943-019-00266-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50495650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sara Bleninger, Michael Fürnrohr, Hans Kiesl, Walter Krämer, Helmut Küchenhoff, Jan Pablo Burgard, Ralf Münnich, Martin Rupp
{"title":"Kommentare und Erwiderung zu: Qualitätszielfunktionen für stark variierende Gemeindegrößen im Zensus 2021","authors":"Sara Bleninger, Michael Fürnrohr, Hans Kiesl, Walter Krämer, Helmut Küchenhoff, Jan Pablo Burgard, Ralf Münnich, Martin Rupp","doi":"10.1007/s11943-019-00264-6","DOIUrl":"10.1007/s11943-019-00264-6","url":null,"abstract":"<div><h2>Zusammenfassung</h2><div><p>Burgard et al. (2020) stellen in ihrem Artikel zu <i>Qualitätszielfunktionen für stark variierende Gemeindegrößen im Zensus 2021</i> Erweiterungen der Stichproben- und Schätzmethoden des Zensus 2011 vor, die kleine Gemeinden unter 10.000 Einwohnern in den Entscheidungsprozess integrieren. Die Dringlichkeit zur Lösung dieses Problems wurde ebenso im Urteil des Bundesverfassungsgerichts zur Volkszählung 2011 festgestellt. Ziel dieser Erwiderung ist eine eingehende Diskussion der Ergebnisse des vorangegangenen Beitrags mit namhaften Experten auf diesem Gebiet. Insbesondere geht es um eine Einordnung des Artikels in den Wissenschaftskontext (Krämer), die Bedeutung von Nichtstichprobenfehlern für den Zensus (Küchenhoff), den Zensus aus Sicht der Amtsstatistik (Bleninger und Fürnrohr) sowie aus statistisch-methodischer Sicht (Kiesl). Darüber hinaus werden aktuelle Entwicklungen vorgestellt.</p></div></div>","PeriodicalId":100134,"journal":{"name":"AStA Wirtschafts- und Sozialstatistisches Archiv","volume":"14 1","pages":"67 - 98"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s11943-019-00264-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50439741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Statistical literacy for classification under risk: an educational perspective","authors":"Laura Martignon, Kathryn Laskey","doi":"10.1007/s11943-019-00259-3","DOIUrl":"10.1007/s11943-019-00259-3","url":null,"abstract":"<div><p>After a brief description of the four components of risk literacy and the tools for analyzing risky situations, decision strategies are introduced, These rules, which satisfy tenets of Bounded Rationality, are called fast and frugal trees. Fast and frugal trees serve as efficient heuristics for decision under risk. We describe the construction of fast and frugal trees and compare their robustness for prediction under risk with that of Bayesian networks. In particular, we analyze situations of risky decisions in the medical domain. We show that the performance of fast and frugal trees does not fall too far behind that of the more complex Bayesian networks.</p></div>","PeriodicalId":100134,"journal":{"name":"AStA Wirtschafts- und Sozialstatistisches Archiv","volume":"13 3-4","pages":"269 - 278"},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s11943-019-00259-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50504071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Anforderungen an eine Statistik-Ausbildung im 21. Jahrhundert vor dem Hintergrund von Statistical (Il‑)Literacy","authors":"Björn Christensen","doi":"10.1007/s11943-019-00263-7","DOIUrl":"10.1007/s11943-019-00263-7","url":null,"abstract":"<div><h2>Zusammenfassung</h2><div><p>Im vorliegenden Beitrag wird anhand von exemplarischen Beispielen aufgeführt, welche Anforderungen an den kompetenzorientierten Umgang mit Statistik gestellt werden sollten und wie sich diese Anforderungen vor dem Hintergrund zunehmender Datenverfügbarkeit mit unterschiedlicher Strukturierungsform (Big Data) verändern. Insbesondere in Fächern, in denen die Statistikausbildung nicht zum Kerninhalt gehört, sollte vorrangig das „Denken in Daten(modellen)“ sowie die Interpretation und Bewertung von Ergebnissen statistischer Berechnungen gelehrt werden.</p></div></div>","PeriodicalId":100134,"journal":{"name":"AStA Wirtschafts- und Sozialstatistisches Archiv","volume":"13 3-4","pages":"193 - 201"},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s11943-019-00263-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50504069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}