TY - GEN A1 - Albrecht, Sophia A1 - Class, Fabian A1 - Feuerstein, Collin A1 - Kohler, Ulrich A1 - Krawietz, Marian T1 - The Potsdam grievance statistics file (PGSF) BT - Codebuch und Methodenbericht N2 - Der Potsdam Grievance Statistics File (PGSF) ist eine historische Datensammlung von Beschwerden, sog. Eingaben, die in der DDR von deren Bürgern eingereicht wurden. Die Eingaben wurden schriftlich oder mündlich gestellt und waren an staatliche Institutionen gerichtet. Der Staat zählte diese Eingaben und kategorisierte sie in Eingabenstatistiken. Der PGSF enthält Eingabenstatistiken des Zeitraums 1970–1989 einer Wahrscheinlichkeitsstichprobe von im Jahr 1990 existierenden Kreisen. Zusätzlich finden sich Eingabenstatistiken eines Convenience-Samples von Kreisen aus dem Zeitraum 1970–1989. Y1 - 2020 U6 - https://doi.org/10.4232/1.13615 ER - TY - GEN A1 - Albrecht, Sophia A1 - Class, Fabian A1 - Goebel, Jan A1 - Kohler, Ulrich A1 - Krawietz, Marian T1 - Leben in der ehemaligen DDR BT - Dokumentation der Daten des Zusatzfragebogens im Rahmen der Befragung “Leben in Deutschland 2018” / Living in the GDR T2 - SOEP Survey Papers Y1 - 2019 PB - German Institute for Economic Research (DIW Berlin) CY - Berlin ER - TY - GEN A1 - Class, Fabian A1 - Kohler, Ulrich A1 - Krawietz, Marian T1 - The Potsdam Grievance Statistics File BT - new data on quality of life and political participation for the German Democratic Republic 1970–1989 T2 - Historical Methods: A Journal of Quantitative and Interdisciplinary History N2 - The newly collected “Potsdam Grievance Statistics File” (PGSF) holds data on the number and topics of grievances (“Eingaben”) that were addressed to local authorities of the German Democratic Republic (GDR) in the years 1970 to 1989. The PGSF allows quantitative analyses on topics such as participation, quality of life, and value change in the German Democratic Republic. This paper introduces the concepts of the data set and discusses the validity of its contents. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 97 KW - Potsdam Grievance Statistics File (PGSF) KW - German Democratic Republic (GDR) KW - Eingaben KW - Participation KW - Quality of Life Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412843 ER - TY - JOUR A1 - Class, Fabian A1 - Köhler, Ulrich A1 - Krawietz, Marian T1 - The Potsdam Grievance Statistics File BT - New data on quality of life and political participation for the German Democratic Republic 1970-1989 JF - Historical Methods N2 - The newly collected Potsdam Grievance Statistics File (PGSF) holds data on the number and topics of grievances (Eingaben) that were addressed to local authorities of the German Democratic Republic (GDR) in the years 1970 to 1989. The PGSF allows quantitative analyses on topics such as participation, quality of life, and value change in the German Democratic Republic. This paper introduces the concepts of the data set and discusses the validity of its contents. KW - Potsdam Grievance Statistics File (PGSF) KW - German Democratic Republic (GDR) KW - Eingaben KW - Participation KW - Quality of Life Y1 - 2018 U6 - https://doi.org/10.1080/01615440.2018.1429970 SN - 0161-5440 SN - 1940-1906 VL - 51 IS - 2 SP - 92 EP - 114 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Kohler, Ulrich A1 - Class, Fabian A1 - Sawert, Tim T1 - Control variable selection in applied quantitative sociology BT - a critical review JF - European sociological review N2 - A review of all research papers published in the European Sociological Review in 2016 and 2017 (N = 118) shows that only a minority of papers clearly define the parameter of interest and provide sufficient reasoning for the selected control variables of the statistical analysis. Thus, the vast majority of papers does not reach minimal standards for the selection of control variables. Consequently, a majority of papers interpret biased coefficients, or statistics without proper sociological meaning. We postulate that authors and reviewers should be more careful about control variable selection. We propose graphical causal models in the form of directed acyclic graphs as an example for a parsimonious and powerful means to that end. Y1 - 2023 U6 - https://doi.org/10.1093/esr/jcac078 SN - 0266-7215 SN - 1468-2672 IS - 20 PB - Oxford Univ. Press CY - Oxford ER - TY - GEN A1 - Krawietz, Marian A1 - Goebel, Jan A1 - Albrecht, Sophia A1 - Class, Fabian A1 - Kohler, Ulrich T1 - Leben in der ehemaligen DDR BT - Zusatzfragebogen im Rahmen der Befragung "Leben in Deutschland 2018" / Living in the GDR Y1 - 2019 U6 - https://doi.org/10.5684/soep.ddr18 PB - German Institute for Economic Research (DIW Berlin) CY - Berlin ER - TY - GEN A1 - Krawietz, Marian A1 - Kohler, Ulrich A1 - Class, Fabian A1 - Albrecht, Sophia A1 - Feuerstein, Collin T1 - The potsdam grievance statistic File (PGSF) BT - Eingabestatistiken der DDR zwischen 1970 und 1989 N2 - Der Potsdam Grievance Statistics File (PGSF) ist eine historische Datensammlung von Beschwerden, sog. Eingaben, die in der DDR von deren Bürgern eingereicht wurden. Die Eingaben wurden schriftlich oder mündlich gestellt und waren an staatliche Institutionen gerichtet. Der Staat zählte diese Eingaben und kategorisierte sie in Eingabenstatistiken. Der PGSF enthält Eingabenstatistiken des Zeitraums 1970–1989 einer Wahrscheinlichkeitsstichprobe von im Jahr 1990 existierenden Kreisen. Zusätzlich finden sich Eingabenstatistiken eines Convenience-Samples von Kreisen aus dem Zeitraum 1970–1989. Y1 - 2020 U6 - https://doi.org/10.4232/1.12993 ER - TY - JOUR A1 - Post, Julia C. A1 - Class, Fabian A1 - Kohler, Ulrich T1 - Unit nonresponse biases in estimates of SARS-CoV-2 prevalence JF - Survey research methods N2 - Since COVID-19 became a pandemic, many studies are being conducted to get a better understanding of the disease itself and its spread. One crucial indicator is the prevalence of SARS-CoV-2 infections. Since this measure is an important foundation for political decisions, its estimate must be reliable and unbiased. This paper presents reasons for biases in prevalence estimates due to unit nonresponse in typical studies. Since it is difficult to avoid bias in situations with mostly unknown nonresponse mechanisms, we propose the maximum amount of bias as one measure to assess the uncertainty due to nonresponse. An interactive web application is presented that calculates the limits of such a conservative unit nonresponse confidence interval (CUNCI). KW - COVID-19 KW - prevalence KW - probability samples KW - unit nonresponse KW - conservative confidence limits KW - nonresponse bias Y1 - 2020 U6 - https://doi.org/10.18148/srm/2020.v14i2.7755 SN - 1864-3361 VL - 14 IS - 2 SP - 115 EP - 121 PB - European Survey Research Association CY - Duisburg ER -