circularity
| 14:49 Aug 21, 2017 |
| Russian to English translations [PRO] Science - Environment & Ecology / фитоценология | |||||
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| 4 +1 | cause and effect argument that takes you back to the cause |
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| 3 | circularity of reasoning |
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Answers
8 mins confidence: 
peer agreement (net): +1
peer agreement (net): +1cause and effect argument that takes you back to the cause Explanation: Definition from MacMillan's Dictionary: "a situation in which a series of causes and effects leads you back to the original cause, producing an argument that does not mean anything". Using values derived from lists, not from work in the field, creates such a situation. |
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11 hrs confidence:
circularity of reasoning Explanation: In a previous study, Zelený & Schaffers (2012) pointed out similar issue with testing the significance of relationship between mean Ellenberg values and scores from ordination diagrams or results of cluster analysis, which was explained by circularity of reasoning. http://www.davidzeleny.net/doku.php/evs2014 cccc . Schaffers. Keywords. Bio-indication; Circularity of reasoning; http://onlinelibrary.wiley.com/doi/10.1111/j.1654-1103.2011.... cccccccccccccccccccccccccccccccc or results of cluster analysis, which was explained by circularity of reasoning. https://www.academia.edu/24363417/Integration_of_European_fo... cccccccc Mean Ellenberg indicator values: too good to be true Leave a reply Zeleny-David-EVS-2012 2I started to think more intensively about Ellenberg indicator values issue at one conference while listening to the presentation, where a colleague used mean Ellenberg indicator values as explanatory variables in constrained ordination. I considered this as a kind of statistical heresy, perfect example of circularity of reasoning – you take your vegetation data, calculate mean Ellenberg indicator values for each plot, and in turn use these mean values to explain the original data. But it’s tempting – mean Ellenberg values are often considered as good proxies for measured environmental variables, and they are easy to calculate, so using them as explanatory variables is attractive. I tried that – I took a dataset with measured soil pH and calculated mean Ellenberg values for soil reaction, and compared how much variation in species data will be explained by pH and how much by mean Ellenberg; Ellenberg was a way better predictor than measured pH. Ok, so here we have the consequence of circularity. Thinking it through, I concluded that the reason is that mean Ellenberg values carry legacy of the species composition, from which they were calculated – if two plots have the same species composition, their mean Ellenberg values will be identical (considering mean not weighted by species covers), and if the species composition differ a bit, Ellenberg will change just slightly (changing one or a few numbers while calculating the mean doesn’t change the result too much). https://davidzeleny.files.wordpress.com/2012/09/zeleny-david... https://davidzeleny.wordpress.com/2012/09/23/ellenberg-value... -------------------------------------------------- Note added at 21 hrs (2017-08-22 12:04:39 GMT) -------------------------------------------------- cccccccccccccccccccc @vasilev: I thought it useful to find the way the author himself describes circularity. Effectively, it appears to be the case of conclusions being built into the starting data: use data to calculate mean Ellenberg indicators, use mean Ellenberg indicators to explain the original data. In the example below, the relationship between soil PH and species composition is calculated. However, mean Ellenberg indicators are corrupted with species composition and cannot be used as independent variables to infer the effect of soil PH on species composition. |
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