What Do You Think? Using Expert Opinion to Improve Predictions of Response Propensity Under a Bayesian Framework.

ABSTRACT: Responsive survey designs introduce protocol changes to survey operations based on accumulating paradata. Case-level predictions, including response propensity, can be used to tailor data collection features in pursuit of cost or quality goals. Unfortunately, predictions based only on partial data from the current round of data collection can be biased, leading to ineffective tailoring. Bayesian approaches can provide protection against this bias. Prior beliefs, which are generated from data external to the current survey implementation, contribute information that may be lacking from the partial current data. Those priors are then updated with the accumulating paradata. The elicitation of the prior beliefs, then, is an important characteristic of these approaches. While historical data fo

SUBMITTER: Coffey S 

PROVIDER: S-EPMC8174793 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature