TY - GEN A1 - Kohler, Ulrich T1 - Editorial: Survey Research Methods during the COVID-19 Crisis T2 - Survey Research Methods KW - COVID-19 KW - Survey Research Methods Y1 - 2020 U6 - https://doi.org/10.18148/srm/2020.v14i2.7769 SN - 1864-3361 VL - 14 IS - 2 SP - 93 EP - 94 CY - Konstanz 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 - 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 - JOUR A1 - Kohler, Ulrich T1 - Survey Research Methods during the COVID-19 Crisis JF - Survey research methods KW - COVID-19 KW - Survey Research Methods Y1 - 2020 U6 - https://doi.org/10.18148/srm/2020.v14i2.7769 SN - 1864-3361 VL - 14 IS - 2 SP - 93 EP - 94 PB - European Survey Research Association CY - Konstanz ER - TY - JOUR A1 - Brady, David A1 - Finnigan, Ryan A1 - Kohler, Ulrich A1 - Legewie, Joscha T1 - The inheritance of race revisited BT - childhood wealth and income and black–white disadvantages in adult life chances JF - Sociological Science N2 - Vast racial inequalities continue to prevail across the United States and are closely linked to economic resources. One particularly prominent argument contends that childhood wealth accounts for black–white (BW) disadvantages in life chances. This article analyzes how much childhood wealth and childhood income mediate BW disadvantages in adult life chances with Panel Study of Income Dynamics and Cross-National Equivalent File data on children from the 1980s and 1990s who were 30+ years old in 2015. Compared with previous research, we exploit longer panel data, more comprehensively assess adult life chances with 18 outcomes, and measure income and wealth more rigorously. We find large BW disadvantages in most outcomes. Childhood wealth and income mediate a substantial share of most BW disadvantages, although there are several significant BW disadvantages even after adjusting for childhood wealth and income. The evidence mostly contradicts the prominent claim that childhood wealth is more important than childhood income. Indeed, the analyses mostly show that childhood income explains more of BW disadvantages and has larger standardized coefficients than childhood wealth. We also show how limitations in prior wealth research explain why our conclusions differ. Replication with the National Longitudinal Survey of Youth and a variety of robustness checks support these conclusions. Y1 - 2020 U6 - https://doi.org/10.15195/v7.a25 SN - 2330-6696 VL - 7 IS - 25 SP - 599 EP - 627 PB - Society for Sociological Science 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 -