@misc{Kohler2020, author = {Kohler, Ulrich}, title = {Editorial: Survey Research Methods during the COVID-19 Crisis}, series = {Survey Research Methods}, volume = {14}, journal = {Survey Research Methods}, number = {2}, address = {Konstanz}, issn = {1864-3361}, doi = {10.18148/srm/2020.v14i2.7769}, pages = {93 -- 94}, year = {2020}, language = {en} } @misc{KrawietzKohlerClassetal.2020, author = {Krawietz, Marian and Kohler, Ulrich and Class, Fabian and Albrecht, Sophia and Feuerstein, Collin}, title = {The potsdam grievance statistic File (PGSF)}, doi = {10.4232/1.12993}, year = {2020}, abstract = {Der Potsdam Grievance Statistics File (PGSF) ist eine historische Datensammlung von Beschwerden, sog. Eingaben, die in der DDR von deren B{\"u}rgern eingereicht wurden. Die Eingaben wurden schriftlich oder m{\"u}ndlich gestellt und waren an staatliche Institutionen gerichtet. Der Staat z{\"a}hlte diese Eingaben und kategorisierte sie in Eingabenstatistiken. Der PGSF enth{\"a}lt Eingabenstatistiken des Zeitraums 1970-1989 einer Wahrscheinlichkeitsstichprobe von im Jahr 1990 existierenden Kreisen. Zus{\"a}tzlich finden sich Eingabenstatistiken eines Convenience-Samples von Kreisen aus dem Zeitraum 1970-1989.}, language = {de} } @misc{AlbrechtClassFeuersteinetal.2020, author = {Albrecht, Sophia and Class, Fabian and Feuerstein, Collin and Kohler, Ulrich and Krawietz, Marian}, title = {The Potsdam grievance statistics file (PGSF)}, doi = {10.4232/1.13615}, year = {2020}, abstract = {Der Potsdam Grievance Statistics File (PGSF) ist eine historische Datensammlung von Beschwerden, sog. Eingaben, die in der DDR von deren B{\"u}rgern eingereicht wurden. Die Eingaben wurden schriftlich oder m{\"u}ndlich gestellt und waren an staatliche Institutionen gerichtet. Der Staat z{\"a}hlte diese Eingaben und kategorisierte sie in Eingabenstatistiken. Der PGSF enth{\"a}lt Eingabenstatistiken des Zeitraums 1970-1989 einer Wahrscheinlichkeitsstichprobe von im Jahr 1990 existierenden Kreisen. Zus{\"a}tzlich finden sich Eingabenstatistiken eines Convenience-Samples von Kreisen aus dem Zeitraum 1970-1989.}, language = {de} } @misc{AlbrechtClassGoebeletal.2020, author = {Albrecht, Sophia and Class, Fabian and Goebel, Jan and Kohler, Ulrich and Krawietz, Marian}, title = {Leben in der ehemaligen DDR}, series = {SOEP Survey Papers}, journal = {SOEP Survey Papers}, publisher = {German Institute for Economic Research (DIW Berlin)}, address = {Berlin}, year = {2020}, language = {de} } @article{Kohler2020, author = {Kohler, Ulrich}, title = {Survey Research Methods during the COVID-19 Crisis}, series = {Survey research methods}, volume = {14}, journal = {Survey research methods}, number = {2}, publisher = {European Survey Research Association}, address = {Konstanz}, issn = {1864-3361}, doi = {10.18148/srm/2020.v14i2.7769}, pages = {93 -- 94}, year = {2020}, language = {en} } @article{BradyFinniganKohleretal.2020, author = {Brady, David and Finnigan, Ryan and Kohler, Ulrich and Legewie, Joscha}, title = {The inheritance of race revisited}, series = {Sociological Science}, volume = {7}, journal = {Sociological Science}, number = {25}, publisher = {Society for Sociological Science}, issn = {2330-6696}, doi = {10.15195/v7.a25}, pages = {599 -- 627}, year = {2020}, abstract = {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.}, language = {en} } @article{PostClassKohler2020, author = {Post, Julia C. and Class, Fabian and Kohler, Ulrich}, title = {Unit nonresponse biases in estimates of SARS-CoV-2 prevalence}, series = {Survey research methods}, volume = {14}, journal = {Survey research methods}, number = {2}, publisher = {European Survey Research Association}, address = {Duisburg}, issn = {1864-3361}, doi = {10.18148/srm/2020.v14i2.7755}, pages = {115 -- 121}, year = {2020}, abstract = {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).}, language = {en} }