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Reporting errors and biases in published empirical findings: Evidence from innovation research

Artikel i vetenskaplig tidskrift
Författare S. B. Bruns
I. Asanov
R. Bode
M. Dunger
C. Funk
S. M. Hassan
J. Hauschildt
D. Heinisch
K. Kempa
J. König
J. Lips
M. Verbeck
E. Wolfschütz
Guido Buenstorf
Publicerad i Research Policy
Volym 48
Nummer/häfte 9
ISSN 0048-7333
Publiceringsår 2019
Publicerad vid Institutionen för ekonomi och samhälle, Innovation and Entrepreneurship (IIE)
Språk en
Länkar dx.doi.org/10.1016/j.respol.2019.05...
Ämnesord Caliper test, Innovation, p-hacking, Publication bias, Reporting bias, Reporting error, Decision making, Personal computing, Empirical findings, Evidence- based decisions, Innovation research, Significance levels, Statistical information, Statistical significance, Errors
Ämneskategorier Ekonomi och näringsliv

Sammanfattning

Errors and biases in published results compromise the reliability of empirical research, posing threats to the cumulative research process and to evidence-based decision making. We provide evidence on reporting errors and biases in innovation research. We find that 45% of the articles in our sample contain at least one result for which the provided statistical information is not consistent with reported significance levels. In 25% of the articles, at least one strong reporting error is diagnosed where a statistically non-significant finding becomes significant or vice versa using the common significance threshold of 0.1. The error rate at the test level is very small with 4.0% exhibiting any error and 1.4% showing strong errors. We also find systematically more marginally significant findings compared to marginally non-significant findings at the 0.05 and 0.1 thresholds of statistical significance. These discontinuities indicate the presence of reporting biases. Explorative analysis suggests that discontinuities are related to authors’ affiliations and to a lesser extent the article's rank in the issue and the style of reporting. © 2019 Elsevier B.V.

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