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Results Repeat Over and Over Again

Written By Thursday, March 17, 2022 Add Comment Edit

Ability of scientific research results to be reproduced past other investigators, supporting the validity

This article is about the reproducibility of scientific inquiry results. For reproductive capacity of organisms, run across fertility and fecundity.

Reproducibility, also known as replicability and repeatability, is a major principle underpinning the scientific method. For the findings of a written report to exist reproducible means that results obtained past an experiment or an observational study or in a statistical analysis of a data set should exist achieved again with a high degree of reliability when the study is replicated. There are different kinds of replication[1] but typically replication studies involve different researchers using the same methodology. Simply later 1 or several such successful replications should a result exist recognized as scientific noesis.

With a narrower scope, reproducibility has been introduced in computational sciences: Whatever results should be documented by making all data and code available in such a way that the computations tin can exist executed again with identical results.

In contempo decades, at that place has been a rise concern that many published scientific results fail the test of reproducibility, evoking a reproducibility or replicability crunch.

History [edit]

Boyle'southward air pump was, in terms of the 17th century, a complicated and expensive scientific apparatus, making reproducibility of results difficult

The first to stress the importance of reproducibility in science was the Irish chemist Robert Boyle, in England in the 17th century. Boyle's air pump was designed to generate and written report vacuum, which at the fourth dimension was a very controversial concept. Indeed, distinguished philosophers such as René Descartes and Thomas Hobbes denied the very possibility of vacuum existence. Historians of scientific discipline Steven Shapin and Simon Schaffer, in their 1985 volume Leviathan and the Air-Pump, draw the debate betwixt Boyle and Hobbes, ostensibly over the nature of vacuum, as fundamentally an statement almost how useful noesis should be gained. Boyle, a pioneer of the experimental method, maintained that the foundations of knowledge should exist constituted by experimentally produced facts, which can exist made believable to a scientific customs past their reproducibility. By repeating the same experiment over and over over again, Boyle argued, the certainty of fact will emerge.

The air pump, which in the 17th century was a complicated and expensive apparatus to build, likewise led to one of the showtime documented disputes over the reproducibility of a item scientific phenomenon. In the 1660s, the Dutch scientist Christiaan Huygens congenital his own air pump in Amsterdam, the first i outside the directly management of Boyle and his assistant at the time Robert Hooke. Huygens reported an effect he termed "dissonant suspension", in which water appeared to levitate in a glass jar within his air pump (in fact suspended over an air chimera), but Boyle and Hooke could not replicate this phenomenon in their own pumps. Every bit Shapin and Schaffer draw, "it became articulate that unless the phenomenon could be produced in England with one of the two pumps available, then no 1 in England would have the claims Huygens had fabricated, or his competence in working the pump". Huygens was finally invited to England in 1663, and nether his personal guidance Hooke was able to replicate anomalous suspension of water. Post-obit this Huygens was elected a Foreign Member of the Regal Society. Even so, Shapin and Schaffer too note that "the achievement of replication was dependent on contingent acts of judgment. 1 cannot write down a formula saying when replication was or was non achieved".[2]

The philosopher of scientific discipline Karl Popper noted briefly in his famous 1934 book The Logic of Scientific Discovery that "not-reproducible single occurrences are of no significance to scientific discipline".[3] The statistician Ronald Fisher wrote in his 1935 book The Design of Experiments, which gear up the foundations for the modern scientific practice of hypothesis testing and statistical significance, that "we may say that a phenomenon is experimentally demonstrable when we know how to deport an experiment which volition rarely fail to give us statistically significant results".[4] Such assertions express a common dogma in modern scientific discipline that reproducibility is a necessary status (although not necessarily sufficient) for establishing a scientific fact, and in practice for establishing scientific authority in any field of knowledge. Withal, every bit noted above by Shapin and Schaffer, this dogma is not well-formulated quantitatively, such as statistical significance for instance, and therefore it is not explicitly established how many times must a fact be replicated to exist considered reproducible.

Terminology [edit]

Replicability and repeatability are related terms broadly or loosely synonymous with reproducibility (for example, among the full general public), but they are frequently usefully differentiated in more than precise senses, as follows.

Ii major steps are naturally distinguished in connection with reproducibility of experimental or observational studies: When new data is obtained in the attempt to achieve information technology, the term replicability is oftentimes used, and the new written report is a replication or replicate of the original one. Obtaining the aforementioned results when analyzing the data fix of the original written report once more with the same procedures, many authors utilise the term reproducibility in a narrow, technical sense coming from its employ in computational research. Repeatability is related to the repetition of the experiment inside the same study by the same researchers. Reproducibility in the original, wide sense is only acknowledged if a replication performed by an independent researcher team is successful.

Unfortunately, the terms reproducibility and replicability sometimes announced even in the scientific literature with reversed meaning,[5] [6] when researchers fail to enforce the more than precise usage.

Measures of reproducibility and repeatability [edit]

In chemical science, the terms reproducibility and repeatability are used with a specific quantitative meaning.[7] In inter-laboratory experiments, a concentration or other quantity of a chemical substance is measured repeatedly in dissimilar laboratories to appraise the variability of the measurements. Then, the standard departure of the difference between two values obtained within the aforementioned laboratory is chosen repeatability. The standard departure for the difference between 2 measurement from different laboratories is chosen reproducibility.[8] These measures are related to the more general concept of variance components in metrology.

Reproducible inquiry [edit]

Reproducible research method [edit]

The term reproducible research refers to the idea that scientific results should exist documented in such a way that their deduction is fully transparent. This requires a detailed description of the methods used to obtain the data[nine] [x] and making the full dataset and the code to calculate the results easily accessible.[eleven] [12] [13] [14] [fifteen] [sixteen] This is the essential part of open science.

To make any inquiry project computationally reproducible, general practice involves all data and files beingness conspicuously separated, labelled, and documented. All operations should be fully documented and automatic as much as practicable, avoiding manual intervention where feasible. The workflow should exist designed as a sequence of smaller steps that are combined then that the intermediate outputs from one step directly feed every bit inputs into the next step. Version control should be used as information technology lets the history of the project be easily reviewed and allows for the documenting and tracking of changes in a transparent manner.

A basic workflow for reproducible research involves data conquering, data processing and data analysis. Data acquisition primarily consists of obtaining master data from a main source such as surveys, field observations, experimental research, or obtaining data from an existing source. Information processing involves the processing and review of the raw information collected in the start stage, and includes data entry, information manipulation and filtering and may be done using software. The data should be digitized and prepared for data analysis. Data may be analysed with the use of software to translate or visualise statistics or data to produce the desired results of the research such as quantitative results including figures and tables. The utilise of software and automation enhances the reproducibility of research methods.[17]

At that place are systems that facilitate such documentation, similar the R Markdown language[18] or the Jupyter notebook.[19] The Open up Science Framework provides a platform and useful tools to support reproducible research.

Reproducible enquiry in practice [edit]

Psychology has seen a renewal of internal concerns about irreproducible results (encounter the entry on replicability crunch for empirical results on success rates of replications). Researchers showed in a 2006 study that, of 141 authors of a publication from the American Psychological Association (APA) empirical articles, 103 (73%) did not answer with their information over a six-month menstruation.[20] In a follow up report published in 2015, it was found that 246 out of 394 contacted authors of papers in APA journals did not share their data upon request (62%).[21] In a 2012 paper, it was suggested that researchers should publish data along with their works, and a dataset was released alongside equally a demonstration.[22] In 2017, an article published in Scientific Data suggested that this may not be sufficient and that the whole analysis context should be disclosed.[23]

In economic science, concerns have been raised in relation to the credibility and reliability of published research. In other sciences, reproducibility is regarded as cardinal and is often a prerequisite to research being published, still in economic sciences information technology is not seen as a priority of the greatest importance. Most peer-reviewed economical journals do not have whatsoever noun measures to ensure that published results are reproducible, however, the top economics journals take been moving to adopt mandatory data and code archives.[24] In that location is low or no incentives for researchers to share their data, and authors would take to conduct the costs of compiling data into reusable forms. Economical research is oftentimes not reproducible equally merely a portion of journals have acceptable disclosure policies for datasets and program code, and even if they do, authors frequently do not comply with them or they are not enforced past the publisher. A Report of 599 manufactures published in 37 peer-reviewed journals revealed that while some journals have accomplished significant compliance rates, significant portion accept only partially complied, or not complied at all. On an article level, the average compliance rate was 47.five%; and on a periodical level, the boilerplate compliance rate was 38%, ranging from xiii% to 99%.[25]

A 2018 study published in the journal PLOS ONE constitute that fourteen.4% of a sample of public health researchers had shared their information or code or both.[26]

There accept been initiatives to improve reporting and hence reproducibility in the medical literature for many years, beginning with the Consort initiative, which is now function of a wider initiative, the EQUATOR Network. This group has recently turned its attention to how better reporting might reduce waste product in research,[27] particularly biomedical research.

Reproducible research is fundamental to new discoveries in pharmacology. A Phase I discovery volition be followed by Stage Ii reproductions as a drug develops towards commercial product. In contempo decades Phase II success has fallen from 28% to 18%. A 2011 study institute that 65% of medical studies were inconsistent when re-tested, and only six% were completely reproducible.[28]

Noteworthy irreproducible results [edit]

Hideyo Noguchi became famous for correctly identifying the bacterial agent of syphilis, just also claimed that he could culture this agent in his laboratory. Nobody else has been able to produce this latter result.[29]

In March 1989, University of Utah chemists Stanley Pons and Martin Fleischmann reported the production of excess oestrus that could only be explained by a nuclear process ("cold fusion"). The written report was astounding given the simplicity of the equipment: information technology was essentially an electrolysis prison cell containing heavy water and a palladium cathode which rapidly absorbed the deuterium produced during electrolysis. The news media reported on the experiments widely, and information technology was a front-page particular on many newspapers around the globe (run into science past press conference). Over the next several months others tried to replicate the experiment, but were unsuccessful.[30]

Nikola Tesla claimed equally early as 1899 to have used a loftier frequency current to calorie-free gas-filled lamps from over 25 miles (xl km) away without using wires. In 1904 he built Wardenclyffe Belfry on Long Island to demonstrate means to send and receive power without connecting wires. The facility was never fully operational and was not completed due to economic problems, so no endeavour to reproduce his first result was ever carried out.[31]

Other examples which reverse testify has refuted the original claim:

  • Stimulus-triggered conquering of pluripotency, revealed to be the result of fraud
  • GFAJ-i, a bacterium that could purportedly incorporate arsenic into its DNA in place of phosphorus
  • MMR vaccine controversy – a study in The Lancet claiming the MMR vaccine acquired autism was revealed to be fraudulent
  • Schön scandal – semiconductor "breakthroughs" revealed to be fraudulent
  • Power posing – a social psychology phenomenon that went viral after beingness the subject of a very pop TED talk, but was unable to be replicated in dozens of studies[32]

See as well [edit]

  • Metascience
  • Accuracy
  • ANOVA gauge R&R
  • Contingency
  • Corroboration
  • Reproducible builds
  • Falsifiability
  • Hypothesis
  • Measurement uncertainty
  • Pathological science
  • Pseudoscience
  • Replication (statistics)
  • Replication crisis
  • ReScience C (journal)
  • Retraction#Notable retractions
  • Tautology
  • Testability
  • Verification and validation

References [edit]

  1. ^ Tsang, Eric West. K.; Kwan, Kai-homo (1999). "Replication and Theory Evolution in Organizational Scientific discipline: A Critical Realist Perspective". Academy of Management Review. 24 (4): 759–780. doi:ten.5465/amr.1999.2553252. ISSN 0363-7425.
  2. ^ Steven Shapin and Simon Schaffer, Leviathan and the Air-Pump, Princeton University Press, Princeton, New Jersey (1985).
  3. ^ This commendation is from the 1959 translation to English language, Karl Popper, The Logic of Scientific Discovery, Routledge, London, 1992, p. 66.
  4. ^ Ronald Fisher, The Blueprint of Experiments, (1971) [1935](9th ed.), Macmillan, p. xiv.
  5. ^ Barba, Lorena A. (2018). "Terminologies for Reproducible Research" (PDF). arXiv:1802.03311 . Retrieved 2020-x-15 .
  6. ^ Liberman, Mark. "Replicability vs. reproducibility — or is it the other way circular?". Retrieved 2020-10-15 .
  7. ^ "IUPAC - reproducibility (R05305)". International Union of Pure and Practical Chemical science . Retrieved 2022-03-04 .
  8. ^ Subcommittee E11.20 on Test Method Evaluation and Quality Command (2014). "Standard Practice for Employ of the Terms Precision and Bias in ASTM Exam Methods". ASTM International. ASTM E177. (subscription required)
  9. ^ King, Gary (1995). "Replication, Replication". PS: Political Science and Politics. 28 (iii): 444–452. doi:10.2307/420301. ISSN 1049-0965. JSTOR 420301.
  10. ^ Kühne, Martin; Liehr, Andreas West. (2009). "Improving the Traditional Information Direction in Natural Sciences". Data Scientific discipline Journal. 8 (1): 18–27. doi:ten.2481/dsj.eight.18.
  11. ^ Fomel, Sergey; Claerbout, Jon (2009). "Guest Editors' Introduction: Reproducible Inquiry". Calculating in Science and Applied science. 11 (1): v–7. Bibcode:2009CSE....11a...5F. doi:10.1109/MCSE.2009.14.
  12. ^ Buckheit, Jonathan B.; Donoho, David L. (May 1995). WaveLab and Reproducible Research (PDF) (Written report). California, Us: Stanford University, Department of Statistics. Technical Report No. 474. Retrieved 5 January 2015.
  13. ^ "The Yale Law School Round Table on Data and Core Sharing: "Reproducible Research"". Calculating in Science and Engineering. 12 (5): eight–12. 2010. doi:10.1109/MCSE.2010.113.
  14. ^ Marwick, Ben (2016). "Computational reproducibility in archaeological research: Bones principles and a case report of their implementation". Periodical of Archaeological Method and Theory. 24 (ii): 424–450. doi:10.1007/s10816-015-9272-nine. S2CID 43958561.
  15. ^ Goodman, Steven North.; Fanelli, Daniele; Ioannidis, John P. A. (1 June 2016). "What does inquiry reproducibility mean?". Science Translational Medicine. 8 (341): 341ps12. doi:x.1126/scitranslmed.aaf5027. PMID 27252173.
  16. ^ Harris J.K; Johnson Thou.J; Combs T.B; Carothers B.J; Luke D.A; Wang X (2019). "Iii Changes Public Wellness Scientists Tin Brand to Assistance Build a Culture of Reproducible Research". Public Health Rep. Public Health Reports. 134 (2): 109–111. doi:ten.1177/0033354918821076. ISSN 0033-3549. OCLC 7991854250. PMC6410469. PMID 30657732.
  17. ^ Kitzes, Justin; Turek, Daniel; Deniz, Fatma (2018). The practice of reproducible research instance studies and lessons from the information-intensive sciences. Oakland, California: University of California Press. pp. 19–thirty. ISBN9780520294745. JSTOR ten.1525/j.ctv1wxsc7.
  18. ^ Marwick, Ben; Boettiger, Carl; Mullen, Lincoln (29 September 2017). "Packaging data analytical work reproducibly using R (and friends)". The American Statistician. 72: 80–88. doi:10.1080/00031305.2017.1375986. S2CID 125412832.
  19. ^ Kluyver, Thomas; Ragan-Kelley, Benjamin; Perez, Fernando; Granger, Brian; Bussonnier, Matthias; Frederic, Jonathan; Kelley, Kyle; Hamrick, Jessica; Grout, Jason; Corlay, Sylvain (2016). "Jupyter Notebooks–a publishing format for reproducible computational workflows" (PDF). In Loizides, F; Schmidt, B (eds.). Positioning and Power in Academic Publishing: Players, Agents and Agendas. 20th International Conference on Electronic Publishing. IOS Printing. pp. 87–xc. doi:x.3233/978-1-61499-649-one-87.
  20. ^ Wicherts, J. 1000.; Borsboom, D.; Kats, J.; Molenaar, D. (2006). "The poor availability of psychological research data for reanalysis". American Psychologist. 61 (seven): 726–728. doi:10.1037/0003-066X.61.7.726. PMID 17032082.
  21. ^ Vanpaemel, W.; Vermorgen, G.; Deriemaecker, Fifty.; Storms, G. (2015). "Are we wasting a good crisis? The availability of psychological research data after the storm". Collabra. i (ane): 1–5. doi:10.1525/collabra.13.
  22. ^ Wicherts, J. M.; Bakker, M. (2012). "Publish (your data) or (allow the data) perish! Why not publish your data besides?". Intelligence. 40 (2): 73–76. doi:10.1016/j.intell.2012.01.004.
  23. ^ Pasquier, Thomas; Lau, Matthew K.; Trisovic, Ana; Boose, Emery R.; Couturier, Ben; Crosas, Mercè; Ellison, Aaron M.; Gibson, Valerie; Jones, Chris R.; Seltzer, Margo (five September 2017). "If these data could talk". Scientific Information. 4: 170114. Bibcode:2017NatSD...470114P. doi:ten.1038/sdata.2017.114. PMC5584398. PMID 28872630.
  24. ^ McCullough, Bruce (March 2009). "Open Access Economics Journals and the Market for Reproducible Economic Research". Economic Assay and Policy. 39 (1): 117–126. doi:10.1016/S0313-5926(09)50047-1.
  25. ^ Vlaeminck, Sven; Podkrajac, Felix (2017-12-10). "Journals in Economic Sciences: Paying Lip Service to Reproducible Research?". IASSIST Quarterly. 41 (1–iv): 16. doi:x.29173/iq6. hdl:11108/359.
  26. ^ Harris, Jenine 1000.; Johnson, Kimberly J.; Carothers, Bobbi J.; Combs, Todd B.; Luke, Douglas A.; Wang, Xiaoyan (2018). "Employ of reproducible inquiry practices in public wellness: A survey of public health analysts". PLOS 1. 13 (9): e0202447. Bibcode:2018PLoSO..1302447H. doi:10.1371/journal.pone.0202447. ISSN 1932-6203. OCLC 7891624396. PMC6135378. PMID 30208041.
  27. ^ "Research Waste/EQUATOR Conference | Research Waste product". researchwaste.cyberspace. Archived from the original on 29 Oct 2016.
  28. ^ Prinz, F.; Schlange, T.; Asadullah, K. (2011). "Believe information technology or non: How much can nosotros rely on published information on potential drug targets?". Nature Reviews Drug Discovery. 10 (ix): 712. doi:10.1038/nrd3439-c1. PMID 21892149.
  29. ^ Tan, SY; Furubayashi, J (2014). "Hideyo Noguchi (1876-1928): Distinguished bacteriologist". Singapore Medical Journal. 55 (10): 550–551. doi:10.11622/smedj.2014140. ISSN 0037-5675. PMC4293967. PMID 25631898.
  30. ^ Browne, Malcolm (iii May 1989). "Physicists Debunk Claim Of a New Kind of Fusion". New York Times . Retrieved 3 February 2017.
  31. ^ Cheney, Margaret (1999), Tesla, Master of Lightning, New York: Barnes & Noble Books, ISBN 0-7607-1005-8, pp. 107.; "Unable to overcome his financial burdens, he was forced to shut the laboratory in 1905."
  32. ^ Dominus, Susan (October 18, 2017). "When the Revolution Came for Amy Cuddy". New York Times Magazine.

Further reading [edit]

  • Timmer, John (October 2006). "Scientists on Scientific discipline: Reproducibility". Ars Technica.
  • Saey, Tina Hesman (January 2015). "Is redoing scientific research the best way to find truth? During replication attempts, too many studies fail to laissez passer muster". Science News. "Science is not irrevocably broken, [epidemiologist John Ioannidis] asserts. It only needs some improvements. "Despite the fact that I've published papers with pretty depressive titles, I'thousand actually an optimist," Ioannidis says. "I find no other investment of a society that is better placed than science.""

External links [edit]

  • Transparency and Openness Promotion Guidelines from the Centre for Open Science
  • Guidelines for Evaluating and Expressing the Dubiousness of NIST Measurement Results of the National Institute of Standards and Applied science
  • Reproducible papers with artifacts by the CTuning foundation
  • ReproducibleResearch.net

wilsonsopen1961.blogspot.com

Source: https://en.wikipedia.org/wiki/Reproducibility

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