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Article Selection

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Please list articles that you're considering for your Wikipedia assignment below. Begin to critique these articles and find relevant sources.

Option 1

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Bland–Altman plot
Article Evaluation
Bland-Altman is a statistical method for comparing two systems. Its focus as a visualization of data and a statistical method for comparison makes it relevant to the data science portion of this course. It's a C-rated article under the Statistics WikiProject. There's a section dedicated to performing the analysis and how to interpret the results, but it doesn't contain a source; Understanding Bland Altman Analysis by Giavarina is a good scholarly article to reference to in this section.:Additionally, there has been extensive coverage on how to use the analysis as a means of using (or not using) a novel method A, which is expected to be compared to an established method B. ::The article glosses over a crucial aspect of the tool however; traditional parametric evaluations of the Limits of Agreement are covered in the original 1986 article, and are covered more extensively in the 1999 article by Bland and Altman. The wikipedia article doesn't mention this. The original articles, as well as Euser's A practical approach to Bland-Altman plots and variation coefficients for log transformed variables would benefit a section on the addition of non-parametric versions of the plot.::The article is written neutrally and very well, it simply doesn't associate some of its points with respective references.:
Sources
[1][2][3]:

Option 2

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Levene's test
Article Evaluation
Laverne's test is a C-rated article apart of the Statistics WikiProject. The article is written neutrally and doesn't have any biased information. There are sentences that may come across as condescending, which should be altered to be more neutral; such as "This test is used because some common statistical procedures assume that variances of the populations from which different samples are drawn are equal," from the first paragraph.::There are pockets of information that could benefit from a reference that establishes the source of the information. For example, there's an entire section that details the Brown-Forsythe test, which although worthy of a mention in its relation as a nonparametric version of the Laverne test, it doesn't reference any of the manuscripts by Brown-Forsythe. ::Additionally, the original article from which the test originated isn't referenced at all.:::
Sources
[4][5]

Option 3

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Backfitting algorithm

Article Evaluation
This article is another C-rated article under the Statistics WikiProject. The article lacks a cohesive use of references; it contains a list of references without citation that directs the source of information in the article. For starters, the article would benefit from sources that back up some of the claims. For example, there's a mention that the algorithm is similar to/comparative to the Gauss-Seidel method, which although true, doesn't have a reference to support it. I included a source that does below. There are several other claims that need citations to support the information; one section alone explains the use cases of the backfitting algorithm without any references -I provided sources that back up those explanations.:
Sources
[6][7][8]

Option 4

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Research design
Article Evaluation
This article is a C-class article apart of the Statistics WikiProject as well as the Science WikiProject. Despite the article being apart of both WikiProjects as well as being a fundamental topic, it lacks a severe amount of citations for the several claims it makes. There are entire sections and paragraphs that don't include a single citation. I included sources below that would provide citation for the information provided.::Additionally, the language used within the article borders on biased and not neutral. There are opinions at several points, notably a mention of particular research methods that are '...bordering on fraud".:
Sources
[9][10][11]

Option 5

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Empirical measure
Article Evaluation
This article is a very basic statistics article, apart of the Statistics WikiProject. It has a severe issue concerning its sources however; there's only one actual reference, with a general list of further reading. The source then, is not credible for the information that it contains.:I included a couple references that provide insight into the information it provides, including the source of the original work that introduced the empirical distribution function, and other references.:The writing at the very least is clear and succinct. The concept is not too complex and therefore matches the complexity in its style by not over-complicating it.:
Sources
[12][13]
  1. ^ Giavarina, Davide (2015-06-15). "Understanding Bland Altman analysis". Biochemia Medica. 25 (2): 141–151. doi:10.11613/BM.2015.015. ISSN 1330-0962.
  2. ^ Kaur, Parampreet; Stoltzfus, Jill C. (2017-06). "Bland–Altman plot: A brief overview". International Journal of Academic Medicine. 3 (1): 110. doi:10.4103/IJAM.IJAM_54_17. {{cite journal}}: Check date values in: |date= (help)CS1 maint: unflagged free DOI (link)
  3. ^ Euser, Anne M.; Dekker, Friedo W.; le Cessie, Saskia (2008-10-01). "A practical approach to Bland-Altman plots and variation coefficients for log transformed variables". Journal of Clinical Epidemiology. 61 (10): 978–982. doi:10.1016/j.jclinepi.2007.11.003. ISSN 0895-4356.
  4. ^ Brown, Morton B.; Forsythe, Alan B. (1974-02-01). "The Small Sample Behavior of Some Statistics Which Test the Equality of Several Means". Technometrics. 16 (1): 129–132. doi:10.1080/00401706.1974.10489158. ISSN 0040-1706.
  5. ^ Brown, Morton B.; Forsythe, Alan B. (1974-06-01). "Robust Tests for the Equality of Variances". Journal of the American Statistical Association. 69 (346): 364–367. doi:10.1080/01621459.1974.10482955. ISSN 0162-1459.
  6. ^ Schimek, Michael G.; Neubauer, Gerhard P.; Stettner, Haro (1994). "Backfitting and related procedures for non-parametric smoothing regression in competition". SFB 373 Discussion Papers.
  7. ^ Cleveland, William S.; Loader, Catherine (1996). Härdle, Wolfgang; Schimek, Michael G. (eds.). "Smoothing by Local Regression: Principles and Methods". Statistical Theory and Computational Aspects of Smoothing. Heidelberg: Physica-Verlag HD: 10–49. doi:10.1007/978-3-642-48425-4_2. ISBN 978-3-642-48425-4.
  8. ^ Ahmed, Syed Ejaz; Aydın, Dursun; Yılmaz, Ersin (2023). "A survey of smoothing techniques based on a backfitting algorithm in estimation of semiparametric additive models". WIREs Computational Statistics. 15 (4): e1605. doi:10.1002/wics.1605. ISSN 1939-0068.
  9. ^ Creswell, John W.; Creswell, J. David (2022-10-18). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. SAGE Publications. ISBN 978-1-0718-1797-1.
  10. ^ Marczyk, Geoffrey R.; DeMatteo, David; Festinger, David (2010-06-03). Essentials of Research Design and Methodology. John Wiley & Sons. ISBN 978-0-470-89353-1.
  11. ^ Hedrick, Terry Elizabeth; Bickman, Leonard; Rog, Debra J. (1993-01-11). Applied Research Design: A Practical Guide. SAGE Publications. ISBN 978-1-5063-1944-5.
  12. ^ Shiryayev, A. N. (1992), Shiryayev, A. N. (ed.), "15. On The Empirical Determination of A Distribution Law", Selected Works of A. N. Kolmogorov: Volume II Probability Theory and Mathematical Statistics, Dordrecht: Springer Netherlands, pp. 139–146, doi:10.1007/978-94-011-2260-3_15, ISBN 978-94-011-2260-3, retrieved 2025-02-23
  13. ^ Brown, Gavin (1983-10). "P. Billingsley, Probability and measure (Wiley, 1979), pp. 532, £28·95". Proceedings of the Edinburgh Mathematical Society. 26 (3): 398–399. doi:10.1017/S0013091500004521. ISSN 1464-3839. {{cite journal}}: Check date values in: |date= (help)
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