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@article{ Kohler2019,
 title = {Possible Uses of Nonprobability Sampling for the Social Sciences},
 author = {Kohler, Ulrich},
 journal = {Survey Methods: Insights from the Field},
 pages = {1-12},
 year = {2019},
 issn = {2296-4754},
 doi = {https://doi.org/10.13094/SMIF-2019-00014},
 abstract = {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.},
 keywords = {Datengewinnung; Szenario; Methodenvergleich; sample; probability; inferential statistics; selection procedure; social science; comparison of methods; Stichprobentheorie; Sozialwissenschaft; schließende Statistik; sampling theory; Stichprobe; survey research; data capture; Selektionsverfahren; Umfrageforschung; Wahrscheinlichkeit; scenario}}