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Re: Citation analysis of author-choice OA journals
- To: liblicense-l@lists.yale.edu
- Subject: Re: Citation analysis of author-choice OA journals
- From: "Stevan Harnad" <amsciforum@gmail.com>
- Date: Wed, 27 Aug 2008 20:44:02 EDT
- Reply-to: liblicense-l@lists.yale.edu
- Sender: owner-liblicense-l@lists.yale.edu
Date: Tue, 26 Aug 2008 07:58:01 -0400 Sender: American Scientist Open Access Forum <AMERICAN-SCIENTIST-OPEN-ACCESS-FORUM@LISTSERVER.SIGMAXI.ORG> From: Stevan Harnad <amsciforum@GMAIL.COM> Subject: Re: Confirmation Bias and the Open Access Advantage: Some Methodological Suggestions for Davis's Citation Study On 25-Aug-08, at 11:01 PM, Phil Davis wrote: > Our study focuses on estimating the effect of author-choice > open access on article citations. The 11 journals were selected > because they gathered sufficient paying open access submissions > as to make a statistical analysis even potentially possible. > Still, if the open access effect is small, a larger sample size > is required to detect a signal amongst the noise, which is why > I aggregated the 11 journals for subsequent analyses. PNAS > contributed so many articles in the aggregate dataset (about a > third) that I didn't want this one journal to skew the results, > hence the tables report the analyses with and without PNAS. Phil: (1) Aggregating the journals was a good idea, to enhance the sample size. (2) But that does not explain why self-archiving OA was not identified and counted in too, instead of crediting all unpaid articles to non-OA (which would of course reduce the size of the OA Advantage). (3) How does the fact that the overall sample was small and the PNAS sample was large justify that the entire PNAS data-set was not analyzed? (I don't contest that it should be analyzed (i) within the aggregate as well as (ii) separately, and that (iii) the rest should also be analyzed separately too, to avoid skewing, I just don't understand why the full analyses were not done and their results reported.) > Secondly, while aggregating the journals resulted in increased > statistical power, we are combining articles published in > *different* scientific fields (biology, medicine, > bioinformatics, plant sciences, and multi-disciplinary > sciences), which is why journal impact factors are not used as > an explanatory variable. Please note that I did include the > variable Journal as either a random variable (Table 2) or a > fixed variable (Table S2), so journal-to-journal variation is > being accounted for in the model Yes, but to the extent that journal variance is included (across mixed fields), it is not at all clear why journal impact-factors should not be included too: After all, different fields may differ not only in their impact factors, but their number of authors, pages, references, Review articles, and US authors. (In our multiple regression analyses, measuring many of the same parameters you did (article age, number of authors, references, etc.), journal impact factor was the second because predictor of citations, after age.) > While I appreciate your routine post-acceptance advice on > methodological improvements, I encourage you to embark on > similar analyses that address your own personal research > interests. The data are all public. (My advice is available pre-acceptance too, if consulted. ;>) ). Analyses addressing my personal research interests will be available shortly, fear not! But the methodological points I made for both your studies -- the BMJ one and this one -- affect the interpretability of your results; they are not just matters of personal taste. http://openaccess.eprints.org/index.php?/archives/451-guid.html http://openaccess.eprints.org/index.php?/archives/441-guid.html To put it another way: You cannot draw the conclusions you draw from your data and your analyses, unless you do some of the further analyses and controls I describe. Cheers, Stevan Stevan Harnad wrote: Confirmation Bias and the Open Access Advantage: Some Methodological Suggestions for Davis's Citation Study Stevan Harnad Full text: http://openaccess.eprints.org/index.php?/archives/451-guid.html SUMMARY: Davis (2008) -- http://arxiv.org/pdf/0808.2428v1 -- analyzes citations from 2004-2007 in 11 biomedical journals. For 1,600 of the 11,000 articles (15%), their authors paid the publisher to make them Open Access (OA). The outcome, confirming previous studies (on both paid and unpaid OA), is a significant OA citation Advantage, but a small one (21%, 4% of it correlated with other article variables such as number of authors, references and pages). The author infers that the size of the OA advantage in this biomedical sample has been shrinking annually from 2004-2007, but the data suggest the opposite. In order to draw valid conclusions from these data, the following five further analyses are necessary: (1) The current analysis is based only on author-choice (paid) OA. Free OA self-archiving needs to be taken into account too, for the same journals and years, rather than being counted as non-OA, as in the current analysis. (2) The proportion of OA articles per journal per year needs to be reported and taken into account. (3) Estimates of journal and article quality and citability in the form of the Journal Impact Factor and the relation between the size of the OA Advantage and journal as well as article "citation-bracket" need to be taken into account. (4) The sample-size for the highest-impact, largest-sample journal analyzed, PNAS, is restricted and is excluded from some of the analyses. An analysis of the full PNAS dataset is needed, for the entire 2004-2007 period. (5) The analysis of the interaction between OA and time, 2004-2007, is based on retrospective data from a June 2008 total cumulative citation count. The analysis needs to be redone taking into account the dates of both the cited articles and the citing articles, otherwise article-age effects and any other real-time effects from 2004-2008 are confounded. The author proposes that an author self-selection bias for providing OA to higher-quality articles (the Quality Bias, QB) is the primary cause of the observed OA Advantage, but this study does not test or show anything at all about the causal role of QB (or of any of the other potential causal factors, such as Accessibility Advantage, AA, Competitive Advantage, CA, Download Advantage, DA, Early Advantage, EA, and Quality Advantage, QA). The author also suggests that paid OA is not worth the cost, per extra citation. This is probably true, but with OA self-archiving, both the OA and the extra citations are free.
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