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How (Not) to Solve the Problem

An Evaluation of Scholarly Responses to Common Source Bias

Dados Bibliográficos

ID7322602
AutoresNathan Favero (0000-0002-8816-088X, Mitchell Institute), Justin B Bullock (0000-0001-6263-2343, Mitchell Institute)
Ano2014
Volume25
Fascículo1
Páginas285-308
Data de publicação2014-05-24
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoJournal of Public Administration Research and Theory (JOURNAL)
Identificadores do periódicoISSN: 1053-1858 • E-ISSN: 1477-9803
EditoraOxford University Press (OUP) (PUBLISHER)
DOI10.1093/jopart/muu020
OpenAlexW2128657319
IdiomaEN
Citações recebidas161
Referências citadas24

Public administration scholars are beginning to pay more attention to the problem of common source bias, but little is known about the approaches that applied researchers are adopting as they attempt to confront the issue in their own research. In this essay, we consider the various responses taken by the authors of six articles in this journal. We draw attention to important nuances of the common measurement issue that have previously received little attention and run a set of empirical analyses in order to test the effectiveness of several proposed solutions to the common-source-bias problem. Our results indicate that none of the statistical remedies being used by public administration scholars appear to be reliable methods of countering the problem. Currently, it appears as though the only reliable solution is to find independent sources of data when perceptual survey measures are employed

Economics · Empirical research · Order (exchange · Perception · Positive economics · Set (abstract data type · Statistics · Computer Science · Electoral Systems and Political Participation · Mathematics · Psychology · Public Policy and Administration Research · Social and Intergroup Psychology

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Obras citantes distintas161
Citações por ano14,64
Intervalo de citações2015 - 2026 (12)
Velocidade de citaçãocurrent
Altamente citadoSim
Tipos de citaçãoNeutras: 161
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