Inferences based on Probability Sampling or Nonprobability Sampling: Are They Nothing but a Question of Models?

Abstract: The inferential quality of an available data set, be it from a probability sample or a nonprobability sample, is discussed under the standard of the representativeness of a sample with regard to interesting characteristics, which implicitly includes the consideration of the total survey error. The paper focuses on the assumptions that are made when calculating an estimator of a certain population characteristic using a specific sampling method, and on the model-based repair methods, which can be applied in the case of deviations from these assumptions. The different implicit assumptions regarding operationalization, frame, selection method, nonresponse, measurement, and data processing are considered exemplarily for the Horvitz-Thompson estimator of a population total. In particular, the remarkable effect of a deviation from the assumption concerning the selection method is discussed. It is shown that there are far more unverifiable, disputable models addressing the different impli

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch
• Notes: Veröffentlichungsversion ; begutachtet (peer reviewed) ; In: Survey Methods: Insights from the Field (2019) ; 1-9

Classification and Topics

• Classification: Mathematik

Contributors, Places and Time

• Event: Veröffentlichung
• (where): Mannheim
• (when): 2019
• Creator: Quatember, Andreas

Further information

• DOI: 10.13094/SMIF-2019-00004
• URN: urn:nbn:de:101:1-2019052813052637936059
• Rights: Open Access; Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 25.03.2025, 1:52 PM CET