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This paper compares the usability of data stemming from probability sampling with data stemming from nonprobability sampling. It develops six research scenarios that differ in their research goals and assumptions about the data generating process. It is shown that inferences from data stemming from nonprobability sampling implies demanding assumptions on the homogeneity of the units being studied. Researchers who are not willing to pose these assumptions are generally better off using data from probability sampling, regardless of the amount of nonresponse. However, even in cases when data from probability sampling is clearly advertised, data stemming from nonprobability sampling may contribute to the cumulative scientific endeavour of pinpointing a plausible interval for the parameter of interest.
This article draws on the experience from an ongoing research project employing respondent-driven sampling (RDS) to survey (illicit) 24-hour home care workers. We highlight issues around the preparatory work and the fielding of the survey to provide researchers with useful insights on how to implement RDS when surveying populations for which the method has not yet been used. We conclude the article with ethical considerations that occur when employing RDS.
Harmonized data file as the basis for comparative analysis of quality of life in the Candidate Countries and the European Union member states, based on seven different data sets, one Eurobarometer survey covering 13 Candidate Countries with an identical set of variables conducted in April 2002, the other six Standard Eurobarometer of different subjects and fielded in different years, each with another set of questions identical with the CC Eurobarometer. Selected aggregate indicators of quality of life ... describing the social situation in the EU15 and Candidate Countries.
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).
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.
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.