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A systematic comparison of methods for combining p-values from independent tests
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Cited by
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Koelstra, S., Muhl, C., Soleymani, M., Lee, J.-S., Yazdani, A., Ebrahimi, T., Pun, T., Nijholt, A., & Patras, I. (2012) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.15 · Cited by 5,093
AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups
Miranda-Correa, J. A., Abadi, M. K., Sebe, N., & Patras, I. (2021) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2884461 · Cited by 709
Are Survey Experiments Externally Valid?
BARABAS, J., & JERIT, J. (2010) · American Political Science Review · doi:10.1017/s0003055410000092 · Cited by 481
The harmonic mean p -value for combining dependent tests
Wilson, D. J. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1814092116 · Cited by 449
Synthesizing and presenting findings using other methods
McKenzie, J. E., & Brennan, S. E. (2019) · Cochrane Handbook for Systematic Reviews of Interventions · doi:10.1002/9781119536604.ch12 · Cited by 423
Metadata
- Authors
- Loughin, T. M.
- Venue
- Computational Statistics & Data Analysis
- Publisher
- Elsevier BV
- Published
- 2004-10
- Volume
- 47
- Issue
- 3
- Pages
- 467-485
- ISSN
- 0167-9473 (ISSN-L)
- OpenAlex
- W2073688165
- Cited by
- 210
- References
- 0
- FWCI
- 3.67
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A systematic comparison of methods for combining p-values from independent tests. https://app.cochat.ai/papers/10.1016/j.csda.2003.11.020
- The paper
- Loughin, T. M. (2004). A systematic comparison of methods for combining p-values from independent tests. Computational Statistics & Data Analysis. https://doi.org/10.1016/j.csda.2003.11.020
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
