{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T08:48:24Z","timestamp":1782204504259,"version":"3.54.5"},"reference-count":85,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100005760","name":"University of Gothenburg","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100005760","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Empir Software Eng"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1007\/s10664-026-10851-1","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T13:47:36Z","timestamp":1776779256000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mitigating omitted variable bias in empirical software engineering"],"prefix":"10.1007","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1040-3201","authenticated-orcid":false,"given":"Carlo A.","family":"Furia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0118-8143","authenticated-orcid":false,"given":"Richard","family":"Torkar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,21]]},"reference":[{"key":"10851_CR1","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.ijar.2022.09.004","volume":"151","author":"A Zanga","year":"2022","unstructured":"Zanga A, Ozkirimli E, Stella F (2022) A survey on causal discovery: Theory and practice. Int J Approx Reason 151:101\u2013129. https:\/\/doi.org\/10.1016\/j.ijar.2022.09.004","journal-title":"Int J Approx Reason"},{"key":"10851_CR2","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1038\/d41586-019-00857-9","volume":"567","author":"V Amrehin","year":"2019","unstructured":"Amrehin V, Greenland S, McShane B (2019) Scientists rise up against statistical significance. Nature 567:305\u2013307","journal-title":"Nature"},{"key":"10851_CR3","doi-asserted-by":"publisher","unstructured":"AndaurNavarro CL, Damen JAA, Takada T, Nijman SWJ, Dhiman P, Ma J, Collins GS, Bajpai R, Riley RD, Moons KGM, Hooft L (2021) Risk of bias in studies on prediction models developed using supervised machine learning techniques: Systematic review. BMJ 375. https:\/\/doi.org\/10.1136\/bmj.n2281","DOI":"10.1136\/bmj.n2281"},{"key":"10851_CR4","doi-asserted-by":"crossref","unstructured":"Clark AG, Foster M, Prifling B, Walkinshaw N, Hierons RM, Schmidt V, Turner RD (2022) Testing causality in scientific modelling software. arXiv preprint arXiv:2209.00357","DOI":"10.1145\/3607184"},{"issue":"434","key":"10851_CR5","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1080\/01621459.1996.10476902","volume":"91","author":"JD Angrist","year":"1996","unstructured":"Angrist JD, Imbens GW, Rubin DB (1996) Identification of causal effects using instrumental variables. J Am Stat Assoc 91(434):444\u2013455. https:\/\/doi.org\/10.1080\/01621459.1996.10476902","journal-title":"J Am Stat Assoc"},{"issue":"2","key":"10851_CR6","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1257\/jep.31.2.3","volume":"31","author":"S Athey","year":"2017","unstructured":"Athey S, Imbens GW (2017) The state of applied econometrics: Causality and policy evaluation. J Econ Perspect 31(2):3\u201332. https:\/\/doi.org\/10.1257\/jep.31.2.3","journal-title":"J Econ Perspect"},{"issue":"2","key":"10851_CR7","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1093\/aje\/kwae153","volume":"194","author":"L Berrie","year":"2025","unstructured":"Berrie L, Arnold KF, Tomova GD, Gilthorpe MS, Tennant PWG (2025) Depicting deterministic variables within directed acyclic graphs: an aid for identifying and interpreting causal effects involving derived variables and compositional data. Am J Epidemiol 194(2):469\u2013479. https:\/\/doi.org\/10.1093\/aje\/kwae153","journal-title":"Am J Epidemiol"},{"key":"10851_CR8","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1038\/s41586-021-04198-4","volume":"600","author":"VC Bradley","year":"2021","unstructured":"Bradley VC, Kuriwaki S, Isakov M, Sejdinovic D, Meng X-L, Flaxman S (2021) Unrepresentative big surveys significantly overestimate US vaccine uptake. Nature 600:695\u2013700. https:\/\/doi.org\/10.1038\/s41586-021-04198-4","journal-title":"Nature"},{"issue":"6280","key":"10851_CR9","doi-asserted-by":"publisher","first-page":"1433","DOI":"10.1126\/science.aaf0918","volume":"351","author":"CF Camerer","year":"2016","unstructured":"Camerer CF, Dreber A, Forsell E, Ho T-H, Huber J, Johannesson M, Kirchler M, Almenberg J, Altmejd A, Chan T, Heikensten E, Holzmeister F, Imai T, Isaksson S, Nave G, Pfeiffer T, Razen M, Hang W (2016) Evaluating replicability of laboratory experiments in economics. Science 351(6280):1433\u20131436. https:\/\/doi.org\/10.1126\/science.aaf0918","journal-title":"Science"},{"key":"10851_CR10","unstructured":"Furia CA, Torkar R(2025) Replication package for: Mitigating omitted variable bias in empirical software engineering. https:\/\/figshare.com\/s\/fe607d8eb7c4cedbac75"},{"key":"10851_CR11","doi-asserted-by":"crossref","unstructured":"Chinn S (2000) A simple method for converting an odds ratio to effect size for use in meta-analysis. Stat Med 19(22):3127\u20133131. https:\/\/doi.org\/10.1002\/1097-0258(20001130)19:22%3C3127::aid-sim784%3E3.0.co;2-m","DOI":"10.1002\/1097-0258(20001130)19:22<3127::AID-SIM784>3.0.CO;2-M"},{"key":"10851_CR12","unstructured":"Cohen J (1988) Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates, 2nd edition"},{"key":"10851_CR13","unstructured":"Cook TD, Campbell DT (1979) Quasi-experimentation: Design & analysis issues for field settings. Houghton Mifflin. ISBN 9780395307908"},{"issue":"1","key":"10851_CR14","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1177\/1471082X15588398","volume":"16","author":"M Dvorzak","year":"2016","unstructured":"Dvorzak M, Wagner H (2016) Sparse Bayesian modelling of underreported count data. Stat Model 16(1):24\u201346. https:\/\/doi.org\/10.1177\/1471082X15588398","journal-title":"Stat Model"},{"key":"10851_CR15","doi-asserted-by":"crossref","unstructured":"Jaynes ET (1976) Confidence intervals vs bayesian intervals. In Harper WL, Hooker CA (eds) Foundations of probability theory, statistical inference, and statistical theories of science. D. Reidel Publishing Company, vol 2, pp 175\u2013257. https:\/\/bayes.wustl.edu\/etj\/articles\/confidence.pdf","DOI":"10.1007\/978-94-010-1436-6_6"},{"issue":"4","key":"10851_CR16","doi-asserted-by":"publisher","first-page":"21:1","DOI":"10.1145\/3340571","volume":"41","author":"ED Berger","year":"2019","unstructured":"Berger ED, Hollenbeck C, Maj P, Vitek O, Vitek J (2019) On the impact of programming languages on code quality: A reproduction study. ACM Trans Program Lang Syst 41(4):21:1-21:24. https:\/\/doi.org\/10.1145\/3340571","journal-title":"ACM Trans Program Lang Syst"},{"issue":"8","key":"10851_CR17","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1109\/TSE.2016.2521368","volume":"42","author":"WE Wong","year":"2016","unstructured":"Wong WE, Gao R, Li Y, Abreu R, Wotawa F (2016) A survey on software fault localization. IEEE Trans Software Eng 42(8):707\u2013740. https:\/\/doi.org\/10.1109\/TSE.2016.2521368","journal-title":"IEEE Trans Software Eng"},{"key":"10851_CR18","doi-asserted-by":"crossref","unstructured":"Fang H, Lamba H, Herbsleb J, Vasilescu B (2022) This is damn slick!\u201d Estimating the impact of tweets on open source project popularity and new contributors. In: Proceedings of the 44th international conference on software engineering, ICSE. ACM","DOI":"10.1145\/3510003.3510121"},{"key":"10851_CR19","unstructured":"Feldt R, Shepperd M, Furia CA, Torkar R (2025) Causal systematic reviews \u2013 synthesizing scientific knowledge through causal links. In preparation"},{"issue":"1","key":"10851_CR20","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1017\/mor.2022.2","volume":"19","author":"CF Fey","year":"2023","unstructured":"Fey CF, Tianyou H, Delios A (2023) The measurement and communication of effect sizes in management research. Manag Organ Rev 19(1):176\u2013197. https:\/\/doi.org\/10.1017\/mor.2022.2","journal-title":"Manag Organ Rev"},{"key":"10851_CR21","unstructured":"Fisher RA (1935) The design of experiments. Oliver & Boyd Edinburgh, Scotland, Edinburgh"},{"key":"10851_CR22","doi-asserted-by":"publisher","unstructured":"Furia CA, Torkar R, Feldt R (2022) Applying Bayesian analysis guidelines to empirical software engineering data: The case of programming languages and code quality. ACM Transactions on Software Engineering and Methodology 31(3). https:\/\/doi.org\/10.1145\/3490953","DOI":"10.1145\/3490953"},{"key":"10851_CR23","doi-asserted-by":"publisher","unstructured":"Furia CA, Torkar R, Feldt R (2023) Towards causal analysis of empirical software engineering data: The impact of programming languages on coding competitions. ACM Trans Softw Eng Methodol 33(1). https:\/\/doi.org\/10.1145\/3611667","DOI":"10.1145\/3611667"},{"key":"10851_CR24","doi-asserted-by":"crossref","unstructured":"Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB (2014) Bayesian data analysis. CRC Press, 3 edition","DOI":"10.1201\/b16018"},{"key":"10851_CR25","doi-asserted-by":"crossref","unstructured":"Baah GK, Podgurski A, Harrold MJ (2010) Causal inference for statistical fault localization. In: Proceedings of the 19th international symposium on Software testing and analysis, pp 73\u201384","DOI":"10.1145\/1831708.1831717"},{"key":"10851_CR26","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1007\/s10664-011-9181-9","volume":"17","author":"JM Gonz\u00e1lez-Barahona","year":"2012","unstructured":"Gonz\u00e1lez-Barahona JM, Robles G (2012) On the reproducibility of empirical software engineering studies based on data retrieved from development repositories. Empir Software Eng 17:75\u201389","journal-title":"Empir Software Eng"},{"key":"10851_CR27","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1146\/annurev.publhealth.22.1.189","volume":"22","author":"S Greenland","year":"2001","unstructured":"Greenland S, Morgenstern H (2001) Confounding in health research. Annu Rev Public Health 22:189\u2013212. https:\/\/doi.org\/10.1146\/annurev.publhealth.22.1.189","journal-title":"Annu Rev Public Health"},{"issue":"1","key":"10851_CR28","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1097\/00001648-199901000-00008","volume":"10","author":"S Greenland","year":"1999","unstructured":"Greenland S, Pearl J, Robins JM (1999) Causal diagrams for epidemiologic research. Epidemiology 10(1):37\u201348","journal-title":"Epidemiology"},{"key":"10851_CR29","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.jss.2016.11.024","volume":"124","author":"L Gren","year":"2017","unstructured":"Gren L, Torkar R, Feldt R (2017) Group development and group maturity when building agile teams: A qualitative and quantitative investigation at eight large companies. J Syst Softw 124:104\u2013119. https:\/\/doi.org\/10.1016\/j.jss.2016.11.024","journal-title":"J Syst Softw"},{"key":"10851_CR30","unstructured":"Halpern J (2015) A modification of the halpern-pearl definition of causality. In: Twenty-fourth international joint conference on artificial intelligence"},{"key":"10851_CR31","doi-asserted-by":"crossref","unstructured":"Heyn H-M, Knauss E (2022) Structural causal models as boundary objects in ai system development. In: 1st International conference on AI engineering-software engineering for AI","DOI":"10.1145\/3522664.3528615"},{"issue":"4","key":"10851_CR32","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1016\/j.bjpt.2018.12.006","volume":"23","author":"L Hespanhol","year":"2019","unstructured":"Hespanhol L, Vallio CS, Costa LM, Saragiotto BT (2019) Understanding and interpreting confidence and credible intervals around effect estimates. Braz J Phys Ther 23(4):290\u2013301. https:\/\/doi.org\/10.1016\/j.bjpt.2018.12.006","journal-title":"Braz J Phys Ther"},{"key":"10851_CR33","doi-asserted-by":"publisher","first-page":"1033","DOI":"10.3758\/BF03213921","volume":"13","author":"R Hoekstra","year":"2014","unstructured":"Hoekstra R, Morey RD, Rouder JN, Wagenmakers E-J (2014) Robust misinterpretation of confidence intervals. Psychon Bull Rev 13:1033\u20131037","journal-title":"Psychon Bull Rev"},{"issue":"8","key":"10851_CR34","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1016\/j.infsof.2014.02.011","volume":"56","author":"NE Holt","year":"2014","unstructured":"Holt NE, Briand LC, Torkar R (2014) Empirical evaluations on the cost-effectiveness of state-based testing: An industrial case study. Inf Softw Technol 56(8):890\u2013910. https:\/\/doi.org\/10.1016\/j.infsof.2014.02.011","journal-title":"Inf Softw Technol"},{"key":"10851_CR35","doi-asserted-by":"publisher","unstructured":"Imbens GW, Wooldridge JM (2009) Recent developments in the econometrics of program evaluation. J Econ Liter 47(1):5\u201386. https:\/\/doi.org\/10.1257\/jel.47.1.5, https:\/\/www.aeaweb.org\/articles?id=10.1257\/jel.47.1.5","DOI":"10.1257\/jel.47.1.5"},{"issue":"4","key":"10851_CR36","doi-asserted-by":"publisher","first-page":"1129","DOI":"10.1257\/jel.20191597","volume":"58","author":"GW Imbens","year":"2020","unstructured":"Imbens GW (2020) Potential outcome and directed acyclic graph approaches to causality: Relevance for empirical practice in economics. J Econ Liter 58(4):1129\u20131179. https:\/\/doi.org\/10.1257\/jel.20191597","journal-title":"J Econ Liter"},{"issue":"5","key":"10851_CR37","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1097\/00001648-200009000-00011","volume":"11","author":"JM Robins","year":"2000","unstructured":"Robins JM, Hern\u00e1n M\u00c1, Brumback B (2000) Marginal structural models and causal inference in epidemiology. Epidemiology 11(5):550\u2013560","journal-title":"Epidemiology"},{"key":"10851_CR38","doi-asserted-by":"publisher","unstructured":"Ioannidis JPA (2005) Why most published research findings are false. PLoS Med 2(8). https:\/\/doi.org\/10.1371\/journal.pmed.0020124","DOI":"10.1371\/journal.pmed.0020124"},{"key":"10851_CR39","doi-asserted-by":"publisher","unstructured":"Hirano K, Imbens GW (2004) The propensity score with continuous treatments. In: Gelman A, Meng X-L (eds) Applied Bayesian modeling and causal inference from incomplete-data perspectives: an essential journey with donald rubin\u2019s statistical family, Wiley Series in Probability and Statistics, chapter Chapter 7, pp 73\u201384. Wiley. https:\/\/doi.org\/10.1002\/0470090456.ch7","DOI":"10.1002\/0470090456.ch7"},{"key":"10851_CR40","doi-asserted-by":"publisher","unstructured":"Bollen KA, Pearl J (2013) Eight myths about causality and structural equation models. In Morgan SL (ed) Handbook of causal analysis for social research, pp 301\u2013328. Springer Netherlands, Dordrecht. https:\/\/doi.org\/10.1007\/978-94-007-6094-3_15","DOI":"10.1007\/978-94-007-6094-3_15"},{"issue":"2","key":"10851_CR41","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1111\/ajps.12417","volume":"63","author":"Kosuke Imai and In Song Kim","year":"2019","unstructured":"Kosuke Imai and In Song Kim (2019) When should we use unit fixed effects regression models for causal inference with longitudinal data? Am J Polit Sci 63(2):467\u2013490. https:\/\/doi.org\/10.1111\/ajps.12417","journal-title":"Am J Polit Sci"},{"issue":"3","key":"10851_CR42","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1145\/2658987","volume":"58","author":"S Krishnamurthi","year":"2015","unstructured":"Krishnamurthi S, Vitek J (2015) The real software crisis: repeatability as a core value. Commun ACM 58(3):34\u201336. https:\/\/doi.org\/10.1145\/2658987","journal-title":"Commun ACM"},{"issue":"1943","key":"10851_CR43","doi-asserted-by":"publisher","first-page":"20202815","DOI":"10.1098\/rspb.2020.2815","volume":"288","author":"ZM Laubach","year":"2021","unstructured":"Laubach ZM, Murray EJ, Hoke KL, Safran RJ, Perng W (2021) A biologist\u2019s guide to model selection and causal inference. Proc R Soc B Biol Sci 288(1943):20202815. https:\/\/doi.org\/10.1098\/rspb.2020.2815","journal-title":"Proc R Soc B Biol Sci"},{"key":"10851_CR44","unstructured":"Lee S, Binkley D, Feldt R, Gold N, Yoo S (2021) Causal program dependence analysis. arXiv preprint arXiv:2104.09107"},{"issue":"4","key":"10851_CR45","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/s10664-024-10456-6","volume":"29","author":"W Lev\u00e9n","year":"2024","unstructured":"Lev\u00e9n W, Broman H, Besker T, Torkar R (2024) The Broken Windows Theory applies to technical debt. Empir Softw Eng 29(4):73. https:\/\/doi.org\/10.1007\/s10664-024-10456-6","journal-title":"Empir Softw Eng"},{"issue":"3","key":"10851_CR46","doi-asserted-by":"publisher","first-page":"948","DOI":"10.2307\/2533848","volume":"54","author":"DY Lin","year":"1998","unstructured":"Lin DY, Psaty BM, Kronmal RA (1998) Assessing the sensitivity of regression results to unmeasured confounders in observational studies. Biometrics 54(3):948\u2013963","journal-title":"Biometrics"},{"key":"10851_CR47","unstructured":"Liu Y, Mattos DI, Bosch J, Olsson HH, Lantz J (2022) Bayesian causal inference in automotive software engineering and online evaluation. arXiv preprint arXiv:2207.00222"},{"issue":"77","key":"10851_CR48","doi-asserted-by":"publisher","first-page":"4495","DOI":"10.21105\/joss.04495","volume":"7","author":"L D\u2019Agostino McGowan","year":"2022","unstructured":"D\u2019Agostino McGowan L (2022) tipr: An R package for sensitivity analyses for unmeasured confounders. J Open Source Softw 7(77):4495. https:\/\/doi.org\/10.21105\/joss.04495","journal-title":"J Open Source Softw"},{"issue":"2","key":"10851_CR49","doi-asserted-by":"publisher","first-page":"1509","DOI":"10.3233\/JIFS-169146","volume":"32","author":"L Madeyski","year":"2017","unstructured":"Madeyski L, Kitchenham B (2017) Would wider adoption of reproducible research be beneficial for empirical software engineering research? J Intell Fuzzy Syst 32(2):1509\u20131521. https:\/\/doi.org\/10.3233\/JIFS-169146","journal-title":"J Intell Fuzzy Syst"},{"key":"10851_CR50","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/j.jss.2015.03.065","volume":"116","author":"M J\u00f8rgensen","year":"2016","unstructured":"J\u00f8rgensen M, Dyb\u00e5 T, Liest\u00f8l K, Sj\u00f8berg DIK (2016) Incorrect results in software engineering experiments: How to improve research practices. J Syst Softw 116:133\u2013145. https:\/\/doi.org\/10.1016\/j.jss.2015.03.065","journal-title":"J Syst Softw"},{"key":"10851_CR51","doi-asserted-by":"publisher","unstructured":"Mathur MB, Smith LH, Ding P, VanderWeele TJ (2021) EValue: Sensitivity analyses for unmeasured confounding and other biases in observational studies and meta-analyses. https:\/\/doi.org\/10.32614\/CRAN.package.EValue","DOI":"10.32614\/CRAN.package.EValue"},{"key":"10851_CR52","doi-asserted-by":"crossref","unstructured":"McElreath R (2020) Statistical rethinking: A Bayesian course with examples in R and Stan, 2nd edn. CRC Press, Florida, USA","DOI":"10.1201\/9780429029608"},{"key":"10851_CR53","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1177\/2053951715602495","volume":"2","author":"D McFarland","year":"2015","unstructured":"McFarland D, McFarland H (2015) Big Data and the danger of being precisely inaccurate. Big Data Soc 2:12. https:\/\/doi.org\/10.1177\/2053951715602495","journal-title":"Big Data Soc"},{"issue":"S1","key":"10851_CR54","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1080\/00031305.2018.1527253","volume":"73","author":"BB McShane","year":"2019","unstructured":"McShane BB, Gal D, Gelman A, Robert C, Tackett JL (2019) Abandon statistical significance. Am Stat 73(S1):235\u2013245","journal-title":"Am Stat"},{"key":"10851_CR55","doi-asserted-by":"publisher","unstructured":"Mehrabi N, Morstatter F, Saxena N, Lerman K, Galstyan A (2021) A survey on bias and fairness in machine learning. ACM Comput Surv 54(6). https:\/\/doi.org\/10.1145\/3457607","DOI":"10.1145\/3457607"},{"key":"10851_CR56","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.infsof.2019.04.005","volume":"112","author":"T Menzies","year":"2019","unstructured":"Menzies T, Shepperd M (2019) \u201cBad smells\u2019\u2019 in software analytics papers. Inf Softw Technol 112:35\u201347","journal-title":"Inf Softw Technol"},{"key":"10851_CR57","doi-asserted-by":"publisher","unstructured":"Morasca S, Russo G (2001) An empirical study of software productivity. In: 25th Annual international computer software and applications conference. COMPSAC 2001, pp 317\u2013322. https:\/\/doi.org\/10.1109\/CMPSAC.2001.960633","DOI":"10.1109\/CMPSAC.2001.960633"},{"key":"10851_CR58","doi-asserted-by":"publisher","unstructured":"Open Science Collaboration (2015) Estimating the reproducibility of psychological science. Science 349(6251):aac4716. https:\/\/doi.org\/10.1126\/science.aac4716","DOI":"10.1126\/science.aac4716"},{"issue":"396","key":"10851_CR59","doi-asserted-by":"publisher","first-page":"945","DOI":"10.2307\/2289064","volume":"81","author":"PW Holland","year":"1986","unstructured":"Holland PW (1986) Statistics and causal inference. J Am Stat Assoc 81(396):945\u2013960. https:\/\/doi.org\/10.2307\/2289064","journal-title":"J Am Stat Assoc"},{"key":"10851_CR60","unstructured":"Pearl J (1982) Reverend Bayes on inference engines: A distributed hierarchical approach. In: Proceedings of the Second AAAI conference on artificial intelligence, AAAI\u201982, pp 133\u2013136. AAAI Press"},{"key":"10851_CR61","doi-asserted-by":"crossref","unstructured":"Pearl J (2009) Causality: Models, reasoning and inference. Cambridge University Press, 2nd edition","DOI":"10.1017\/CBO9780511803161"},{"issue":"4","key":"10851_CR62","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1007\/s10664-022-10148-z","volume":"27","author":"B Penzenstadler","year":"2022","unstructured":"Penzenstadler B, Torkar R, Martinez Montes C (2022) Take a deep breath: Benefits of neuroplasticity practices for software developers and computer workers in a family of experiments. Empir Softw Eng 27(4):98. https:\/\/doi.org\/10.1007\/s10664-022-10148-z","journal-title":"Empir Softw Eng"},{"issue":"2","key":"10851_CR63","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1093\/ije\/dyaa213","volume":"50","author":"PWG Tennant","year":"2021","unstructured":"Tennant PWG, Murray EJ, Arnold KF, Berrie L, Fox MP, Gadd SC, Harrison WJ, Keeble C, Ranker LR, Textor J, Tomova GD, Gilthorpe MS, Ellison GTH (2021) Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations. Int J Epidemiol 50(2):620\u2013632. https:\/\/doi.org\/10.1093\/ije\/dyaa213","journal-title":"Int J Epidemiol"},{"key":"10851_CR64","doi-asserted-by":"publisher","unstructured":"Ray B, Posnett D, Filkov V, Devanbu P (2014) A large scale study of programming languages and code quality in Github. In: Proceedings of the 22nd ACM SIGSOFT international symposium on foundations of software engineering, FSE 2014, pages 155\u2013165, New York, NY, USA. Association for Computing Machinery. https:\/\/doi.org\/10.1145\/2635868.2635922","DOI":"10.1145\/2635868.2635922"},{"issue":"2","key":"10851_CR65","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1007\/s10664-024-10475-3","volume":"29","author":"M Rezaalipour","year":"2024","unstructured":"Rezaalipour M, Furia CA (2024) An empirical study of fault localization in Python programs. Empir Softw Eng 29(2):92","journal-title":"Empir Softw Eng"},{"key":"10851_CR66","doi-asserted-by":"crossref","unstructured":"Wasserstein RL, Lazar NA (2016) The ASA statement on $$p$$-values: Context, process, and purpose. Am Stat 70(2):129\u2013133. https:\/\/www.amstat.org\/asa\/files\/pdfs\/P-ValueStatement.pdf","DOI":"10.1080\/00031305.2016.1154108"},{"issue":"5","key":"10851_CR67","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1037\/h0037350","volume":"66","author":"DB Rubin","year":"1974","unstructured":"Rubin DB (1974) Estimating causal effects of treatments in randomized and nonrandomized studies. J Educ Psychol 66(5):688\u2013701","journal-title":"J Educ Psychol"},{"key":"10851_CR68","unstructured":"Sagan C (1986) Broca\u2019s brain: reflections on the romance of science. Random house publishing group, ISBN 9780345336897"},{"issue":"8","key":"10851_CR69","doi-asserted-by":"publisher","first-page":"e1787","DOI":"10.1002\/stvr.1787","volume":"31","author":"M Scholz","year":"2021","unstructured":"Scholz M, Torkar R (2021) An empirical study of linespots: A novel past-fault algorithm. Softw Test Verif Reliab 31(8):e1787","journal-title":"Softw Test Verif Reliab"},{"key":"10851_CR70","doi-asserted-by":"crossref","unstructured":"Siebert J (2022) Applications of statistical causal inference in software engineering. arXiv preprint arXiv:2211.11482","DOI":"10.1016\/j.infsof.2023.107198"},{"key":"10851_CR71","doi-asserted-by":"crossref","unstructured":"Spirtes P, Zhang K (2016) Causal discovery and inference: concepts and recent methodological advances. In: Applied informatics, vol 3, pp 1\u201328. SpringerOpen","DOI":"10.1186\/s40535-016-0018-x"},{"issue":"4","key":"10851_CR72","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1214\/ss\/1177012031","volume":"5","author":"J Splawa-Neyman","year":"1990","unstructured":"Splawa-Neyman J, Dabrowska DM, Speed TP (1990) On the application of probability theory to agricultural. Experiments essay on principles. Section 9. Stat Sci 5(4):465\u2013472. https:\/\/doi.org\/10.1214\/ss\/1177012031","journal-title":"Stat Sci"},{"issue":"1","key":"10851_CR73","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1214\/09-STS313","volume":"25","author":"EA Stuart","year":"2010","unstructured":"Stuart EA (2010) Matching methods for causal inference: A review and a look forward. Stat Sci 25(1):1\u201321","journal-title":"Stat Sci"},{"key":"10851_CR74","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1038\/s41390-018-0071-3","volume":"84","author":"TC Williams","year":"2018","unstructured":"Williams TC, Bach CC, Matthiesen NB, Henriksen TB, Gagliardi L (2018) Directed acyclic graphs: a tool for causal studies in paediatrics. Pediatr Res 84:487\u2013493. https:\/\/doi.org\/10.1038\/s41390-018-0071-3","journal-title":"Pediatr Res"},{"issue":"6","key":"10851_CR75","doi-asserted-by":"publisher","first-page":"2053","DOI":"10.1109\/TSE.2020.3048991","volume":"48","author":"R Torkar","year":"2022","unstructured":"Torkar R, Furia CA, Feldt R, Gomes de Oliveira Neto F, Gren L, Lenberg P, Ernst NA (2022) A method to assess and argue for practical significance in software rngineering. IEEE Trans Software Eng 48(6):2053\u20132065. https:\/\/doi.org\/10.1109\/TSE.2020.3048991","journal-title":"IEEE Trans Software Eng"},{"key":"10851_CR76","doi-asserted-by":"publisher","unstructured":"Tsunoda M, Ono K (2014) Pitfalls of analyzing a cross-company dataset of software maintenance and support. In: 15th IEEE\/ACIS international conference on software engineering, artificial intelligence, networking and parallel\/distributed computing, SNPD 2014, Las Vegas, NV, USA, June 30 - July 2, 2014, pp 1\u20136. IEEE Computer Society. https:\/\/doi.org\/10.1109\/SNPD.2014.6888729","DOI":"10.1109\/SNPD.2014.6888729"},{"issue":"6","key":"10851_CR77","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0000000000000733","volume":"28","author":"TJ VanderWeele","year":"2017","unstructured":"VanderWeele TJ (2017) On a square-root transformation of the odds ratio for a common outcome. Epidemiology 28(6):e58. https:\/\/doi.org\/10.1097\/EDE.0000000000000733","journal-title":"Epidemiology"},{"issue":"4","key":"10851_CR78","first-page":"268","volume":"167","author":"TJ VanderWeele and Peng Ding","year":"2011","unstructured":"TJ VanderWeele and Peng Ding (2011) Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med 167(4):268\u2013274","journal-title":"Ann Intern Med"},{"issue":"2","key":"10851_CR79","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1093\/biomet\/2.2.121","volume":"2","author":"GU Yule","year":"1903","unstructured":"Yule GU (1903) Notes on the theory of association of attributes in statistics. Biometrika 2(2):121\u2013134. https:\/\/doi.org\/10.1093\/biomet\/2.2.121","journal-title":"Biometrika"},{"issue":"4","key":"10851_CR80","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1214\/14-STS493","volume":"29","author":"S Vansteelandt","year":"2014","unstructured":"Vansteelandt S, Joffe M (2014) Structural nested models and g-estimation: The partially realized promise. Stat Sci 29(4):707\u2013731. https:\/\/doi.org\/10.1214\/14-STS493","journal-title":"Stat Sci"},{"issue":"5","key":"10851_CR81","doi-asserted-by":"publisher","first-page":"1413","DOI":"10.1007\/s11222-016-9696-4","volume":"27","author":"A Vehtari","year":"2017","unstructured":"Vehtari A, Gelman A, Gabry J (2017) Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput 27(5):1413\u20131432. https:\/\/doi.org\/10.1007\/s11222-016-9696-4","journal-title":"Stat Comput"},{"key":"10851_CR82","doi-asserted-by":"publisher","unstructured":"Wang H, Wang H, Zhang H (2008) Software productivity analysis with CSBSG data set. In: International conference on computer science and software engineering, CSSE 2008, Volume 2: Software Engineering, December 12-14, 2008, Wuhan, China, pages 587\u2013593. IEEE Computer Society. https:\/\/doi.org\/10.1109\/CSSE.2008.1178","DOI":"10.1109\/CSSE.2008.1178"},{"key":"10851_CR83","first-page":"3571","volume":"11","author":"S Watanabe","year":"2010","unstructured":"Watanabe S (2010) Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory. J Mach Learn Res 11:3571\u20133594","journal-title":"J Mach Learn Res"},{"key":"10851_CR84","doi-asserted-by":"publisher","unstructured":"Wohlin C, Runeson P, H\u00f6st M, Ohlsson MC, Regnell B (2012). Experimentation in software engineering Springer. https:\/\/doi.org\/10.1007\/978-3-642-29044-2","DOI":"10.1007\/978-3-642-29044-2"},{"issue":"2","key":"10851_CR85","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1109\/TSE.2019.2892102","volume":"47","author":"D Zou","year":"2021","unstructured":"Zou D, Liang J, Xiong Y, Ernst MD, Zhang L (2021) An empirical study of fault localization families and their combinations. IEEE Trans Software Eng 47(2):332\u2013347. https:\/\/doi.org\/10.1109\/TSE.2019.2892102","journal-title":"IEEE Trans Software Eng"}],"container-title":["Empirical Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10664-026-10851-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10664-026-10851-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10664-026-10851-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T08:01:44Z","timestamp":1782201704000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10664-026-10851-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,21]]},"references-count":85,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["10851"],"URL":"https:\/\/doi.org\/10.1007\/s10664-026-10851-1","relation":{},"ISSN":["1382-3256","1573-7616"],"issn-type":[{"value":"1382-3256","type":"print"},{"value":"1573-7616","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,21]]},"assertion":[{"value":"22 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed Consent"}},{"value":"The authors hereby unequivocally affirm that they are, to the best of their knowledge, unencumbered by any competing financial, professional, or personal interests of whatsoever nature that might, directly or indirectly, bear upon, be construed as influencing, or otherwise pertain to the research and findings herein presented.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Clinical Trial Number"}}],"article-number":"123"}}