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Very interesting topic imho.
> Make sure you read contributions from both "sides", including [...]
Michał, maybe you could add these references as another update of your blog post.
Christophe Prieur, [log in to unmask]
Liafa, Université Paris-Diderot http://liafa.fr/~prieur/
[user experience research, social networks, (large) graph algorithms]
Le 8 juin 2011 à 11:07, Michał Bojanowski a écrit :
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> Thanks. It is an interesting article indeed
> (in fact it was available trough ArXiv since July 2010,
> The issue revolved into an interesting debate. Partly covered here
> I blogged about it too
> Make sure you read contributions from both "sides", including
> Fowler, James H. and Nicholas A. Christakis. 2008b. “Estimating peer
> effects on health in social networks: A response to Cohen-Cole and
> Fletcher and Trogdon, Nonnemaker, and Pais.” Journal of Health Eco-
> nomics 27:1400–1405.
> and also a recent related paper by Noel & Nyhan
> "The “Unfriending” Problem The Consequences of Homophily in Friendship
> Retention for Causal Estimates of Social Influence"
> On Wed, Jun 8, 2011 at 7:57 AM, Ilan Talmud <[log in to unmask]> wrote:
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>> Lyons, Russell (2011) "The Spread of Evidence-Poor Medicine via Flawed
>> Social-Network Analysis," Statistics, Politics, and Policy: Vol. 2: Iss. 1,
>> Article 2.
>> DOI: 10.2202/2151-7509.1024
>> Available at: http://www.bepress.com/spp/vol2/iss1/2Abstract
>> The chronic widespread misuse of statistics is usually inadvertent, not
>> intentional. We find cautionary examples in a series of recent papers by
>> Christakis and Fowler that advance statistical arguments for the
>> transmission via social networks of various personal characteristics,
>> including obesity, smoking cessation, happiness, and loneliness. Those
>> papers also assert that such influence extends to three degrees of
>> separation in social networks. We shall show that these conclusions do not
>> follow from Christakis and Fowler's statistical analyses. In fact, their
>> studies even provide some evidence against the existence of such
>> transmission. The errors that we expose arose, in part, because the
>> assumptions behind the statistical procedures used were insufficiently
>> examined, not only by the authors, but also by the reviewers. Our examples
>> are instructive because the practitioners are highly reputed, their results
>> have received enormous popular attention, and the journals that published
>> their studies are among the most respected in the world. An educational
>> bonus emerges from the difficulty we report in getting our critique
>> published. We discuss the relevance of this episode to understanding
>> statistical literacy and the role of scientific review, as well as to
>> reforming statistics education
>> ... summarizing the major problems with C&F’s studies:
>> 1. The data are not available to others.
>> 2. The unavailable data are sparse for friendships.
>> 3. The models used to analyze the sparse data contradict the data and the
>> 4. The method used to estimate the dubious models does not apply.
>> 5. The statistical significance tests from the questionable estimates do not
>> the proposed differences.
>> 6. The wrongly proposed differences do not distinguish among homophily,
>> and induction.
>> 7. Associations at a distance are better explained by homophily than by
>> Prof. Ilan Talmud, Ph.D.
>> Head, Economic Sociology, Department of Sociology and Anthropology,
>> University of Haifa
>> Phones: 972-4-8240992 (office direct)
>> 972-4-8240995 / 8249505 (secretaries)
>> (cell) 972-522-220914 Fax: 972-4-8240819
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