Analysis code and result data for "Non-specific between-drug differences in the FDA Adverse Event Reporting System are large and ubiquitous: an empirical-null audit of 26 drug pairs"

This record contains the complete analysis pipeline and every result file underlying the study"Non-specific between-drug differences in the FDA Adverse Event Reporting System are large andubiquitous: an empirical-null audit of 26 drug pairs". Contents: S_code/ (47 Python scripts and a pinned requirements file, implementing FAERS ingest anddeduplication, empirical-null panel construction, random-effects and false-discovery-rate testing,bootstrap calibration, time-to-onset analysis, and the JADER replication); S_data/ (48 CSV tables ofpanel estimates, formal test results, sensitivity analyses and JADER replication outputs); README.md(re-analysis guide); and REPLICATION_PROTOCOL.md (the pre-specified JADER replication plan writtenbefore the data were accessed). The underlying source data are public and are not redistributed here: the FDA FAERS quarterly extracts(faers_ascii_2016q1.zip through faers_ascii_2026q2.zip, downloaded 2026-09-17) fromhttps://fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html, and the PMDA JADER releasepmdacasereport202609 (1,054,239 cases) from https://www.info.pmda.go.jp/fukusayoudb/CsvDownload.jsp. Code is released under the MIT License; the CSV result tables are released under CC-BY 4.0.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-16
DOI
https://doi.org/10.5281/zenodo.23409295
Primary Topic
Pharmacovigilance and Adverse Drug Reactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis code and result data for "Non-specific between-drug differences in the FDA Adverse Event Reporting System are large and ubiquitous: an empirical-null audit of 26 drug pairs"

Zhiwei Liu, Xue Yang, Bo Dong, Qian Chen et al.
Zenodo (CERN European Organization for Nuclear Research)
Pharmacovigilance and Adverse Drug Reactions
article

Analysis code and result data for "Non-specific between-drug differences in the FDA Adverse Event Reporting System are large and ubiquitous: an empirical-null audit of 26 drug pairs"

Zhiwei Liu, Xue Yang, Bo Dong, Qian Chen, Qian Sun, Jiahao Zhao, Xiaoqing Diao
article en

Abstract

This record contains the complete analysis pipeline and every result file underlying the study"Non-specific between-drug differences in the FDA Adverse Event Reporting System are large andubiquitous: an empirical-null audit of 26 drug pairs". Contents: S_code/ (47 Python scripts and a pinned requirements file, implementing FAERS ingest anddeduplication, empirical-null panel construction, random-effects and false-discovery-rate testing,bootstrap calibration, time-to-onset analysis, and the JADER replication); S_data/ (48 CSV tables ofpanel estimates, formal test results, sensitivity analyses and JADER replication outputs); README.md(re-analysis guide); and REPLICATION_PROTOCOL.md (the pre-specified JADER replication plan writtenbefore the data were accessed). The underlying source data are public and are not redistributed here: the FDA FAERS quarterly extracts(faers_ascii_2016q1.zip through faers_ascii_2026q2.zip, downloaded 2026-09-17) fromhttps://fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html, and the PMDA JADER releasepmdacasereport202609 (1,054,239 cases) from https://www.info.pmda.go.jp/fukusayoudb/CsvDownload.jsp. Code is released under the MIT License; the CSV result tables are released under CC-BY 4.0.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 12%
Pharmacovigilance and Adverse Drug Reactions
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