Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-27T13:01:49.598Z Has data issue: false hasContentIssue false

Raw data + analysis code > descriptive statistics

Published online by Cambridge University Press:  14 December 2021

Cort W. Rudolph*
Affiliation:
Saint Louis University
Hannes Zacher
Affiliation:
Leipzig University
*
*Corresponding author. Email: cort.rudolph@health.slu.edu

Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Commentaries
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the Society for Industrial and Organizational Psychology

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Cort W. Rudolph, Department of Psychology, Saint Louis University, St. Louis, MO (USA). Hannes Zacher, Institute of Psychology–Wilhelm Wundt, Leipzig University, Leipzig, Germany.

References

Bishop, D. (2015, December 15). Who’s afraid of open data: Scientists’ objections to data sharing don’t stand up to scrutiny. LSE Impact Blog. https://blogs.lse.ac.uk/impactofsocialsciences/2015/12/16/whos-afraid-of-open-data-dorothy-bishop/ Google Scholar
Curran, P. J., & Hussong, A. M. (2009). Integrative data analysis: The simultaneous analysis of multiple data sets. Psychological Methods, 14(2), 81100. https://doi.org/10.1037/a0015914 CrossRefGoogle ScholarPubMed
Eisenhauer, J. G. (2021). Meta-analysis and mega-analysis: Asimple introduction. Teaching Statistics, 43(1), 2127. https://doi.org/10.1111/test.12242 CrossRefGoogle Scholar
Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings. SAGE.10.4135/9781412985031CrossRefGoogle Scholar
Katz, I. M., Rudolph, C. W., & Zacher, H. (2019). Age and career commitment: Meta-analytic tests of competing linear versus curvilinear relationships. Journal of Vocational Behavior, 112, 396416. https://doi.org/10.1016/j.jvb.2019.03.001 CrossRefGoogle Scholar
Laine, H. (2017). Afraid of scooping–case study on researcher strategies against fear of scooping in the context of open science. Data Science Journal, 16, 29. http://doi.org/10.5334/dsj-2017-029 CrossRefGoogle Scholar
Levelt, P., Noort, E., & Drenth, P. (2012). Flawed science: The fraudulent research practices of social psychologist Diederik Stapel. Tilburg University. https://www.rug.nl/about-ug/latest-news/news/archief2012/nieuwsberichten/stapel-eindrapport-eng.pdf Google Scholar
Murphy, K. (2021). In praise of Table 1: The importance of making better use of descriptive statistics. Industrial and Organizational Psychology: Perspectives on Science and Practice, 14(4), 461477.Google Scholar
Nowok, B., Raab, G. M., & Dibben, C. (2016). synthpop: Bespoke creation of synthetic data in R. Journal of Statistical Software, 74(11), 126. https://doi.org/10.18637/jss.v074.i11 CrossRefGoogle Scholar
Poldrack, R. A., & Poline, J. B. (2015). The publication and reproducibility challenges of shared data. Trends in Cognitive Sciences, 19(2), 5961. https://doi.org/10.1016/j.tics.2014.11.008 CrossRefGoogle ScholarPubMed
Rudolph, C., & Jundt, D. (2017, July 18). Why betas should not rule metas. PsyArXiv. https://doi.org/10.31234/osf.io/jacdy CrossRefGoogle Scholar
Rudolph, C. W. (2021). Improving careers science: Ten recommendations to enhance the credibility of vocational behavior research. Journal of Vocational Behavior, 126, Article 103560. https://doi.org/10.1016/j.jvb.2021.103560 CrossRefGoogle Scholar
Schmidt, F., & Hunter, J. (2002). Are there benefits from NHST? American Psychologist, 57(1), 6566. https://doi.org/10.1037/0003-066X.57.1.65 CrossRefGoogle ScholarPubMed
Silberzahn, R., Simonsohn, U., & Uhlmann, E. L. (2014). Matched-names analysis reveals no evidence of name-meaning effects: Acollaborative commentary on Silberzahn and Uhlmann (2013). Psychological Science, 25(7), 15041505. https://doi.org/10.1177/0956797614533802 CrossRefGoogle Scholar
Simonsohn, U. (2013). Just post it: The lesson from two cases of fabricated data detected by statistics alone. Psychological Science, 24(10), 18751888. https://doi.org/10.1177/0956797613480366 CrossRefGoogle ScholarPubMed