Two Wrongs Make a Right: Addressing Underreporting in Binary Data from Multiple Sources.

ABSTRACT: Media-based event data-i.e., data comprised from reporting by media outlets-are widely used in political science research. However, events of interest (e.g., strikes, protests, conflict) are often underreported by these primary and secondary sources, producing incomplete data that risks inconsistency and bias in subsequent analysis. While general strategies exist to help ameliorate this bias, these methods do not make full use of the information often available to researchers. Specifically, much of the event data used in the social sciences is drawn from multiple, overlapping news sources (e.g., Agence France-Presse, Reuters). Therefore, we propose a novel maximum likelihood estimator that corrects for misclassification in data arising from multiple sources. In the most general formulation

SUBMITTER: Cook SJ 

PROVIDER: S-EPMC5667662 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature