On the Impact of Response Patterns on Survey Estimates from Access Panels

Enderle, Tobias; Münnich, Ralf; Bruch, Christiane

doi:10.18148/srm/2013.v7i2.5036

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2022

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Cited by 2 publications

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“…The inclusion mechanism is simulated using the following procedure (the modeling of y U and the inclusion mechanism to create the volunteer sample is done on the basis of the procedure to model the nonresponse mechanism in the simulation study of Enderle, Münnich, and Bruch (2013)):…”

Section: Simulation Studymentioning

confidence: 99%

Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study.

Bruch¹,

Felderer²

2022

AJS

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The multilevel and poststratification approach is commonly used to draw valid inference from (non-probabilistic) surveys. This Bayesian approach includes varying regression coefficients for which prior distributions of their variance parameter must be specified. The choice of the distribution is far from being trivial and many contradicting recommendations exist in the literature. The prior choice may be even more challenging when data results from a highly selective inclusion mechanism, such as applied by volunteer panels. We conduct a Monte Carlo simulation study to evaluate the effect of different distribution choices on bias in the estimation of a proportion based on a sample that is subject to a highly selective inclusion mechanism.

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Section: Simulation Studymentioning

confidence: 99%