andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-756 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: After I posted on Russ Lyons’s criticisms of the work of Nicholas Christakis and James Fowler’s work on social networks, several people emailed in with links to related articles. (Nobody wants to comment on the blog anymore; all I get is emails.) Here they are: Political scientists Hans Noel and Brendan Nyhan wrote a paper called “The ‘Unfriending’ Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence” in which they argue that the Christakis-Fowler results are subject to bias because of patterns in the time course of friendships. Statisticians Cosma Shalizi and AT wrote a paper called “Homophily and Contagion Are Generically Confounded in Observational Social Network Studies” arguing that analyses such as those of Christakis and Fowler cannot hope to disentangle different sorts of network effects. And Christakis and Fowler reply to Noel and Nyhan, Shalizi and Thomas, Lyons, and others in an article that begins: H
sentIndex sentText sentNum sentScore
1 After I posted on Russ Lyons’s criticisms of the work of Nicholas Christakis and James Fowler’s work on social networks, several people emailed in with links to related articles. [sent-1, score-0.369]
2 Statisticians Cosma Shalizi and AT wrote a paper called “Homophily and Contagion Are Generically Confounded in Observational Social Network Studies” arguing that analyses such as those of Christakis and Fowler cannot hope to disentangle different sorts of network effects. [sent-4, score-0.642]
3 We do not claim that this work is definitive, but we do think that it provides some novel sorts of evidence regarding social contagion in longitudinally followed networks. [sent-7, score-0.613]
4 Along with other scholars, we are working to develop new methods for identifying causal effects using social network data. [sent-8, score-0.542]
5 This was about what I was imagining: the work is not definitive but they have found some patterns in this particular idiosyncratic dataset and it will be interesting to see what comes next. [sent-9, score-0.494]
6 Finally, Lyons wrote in his paper that the Christakis-Fowler data are “are not available to others. [sent-10, score-0.16]
7 ” That’s not completely correct; at the time of the writing of his paper Lyons was unaware of this online data source (apparently googlable from “framingham social network data”). [sent-11, score-0.62]
8 Unfortunately, confidentiality restrictions appear to limit the data in such a way that only partial replications can be done using this public dataset. [sent-12, score-0.225]
wordName wordTfidf (topN-words)
[('lyons', 0.341), ('contagion', 0.234), ('social', 0.231), ('network', 0.23), ('christakis', 0.23), ('fowler', 0.219), ('noel', 0.202), ('homophily', 0.19), ('framingham', 0.17), ('nyhan', 0.146), ('influence', 0.145), ('definitive', 0.141), ('shalizi', 0.125), ('networks', 0.117), ('observational', 0.114), ('dataset', 0.105), ('disentangle', 0.101), ('regularities', 0.101), ('retention', 0.101), ('affective', 0.095), ('generically', 0.095), ('russ', 0.095), ('patterns', 0.091), ('friendship', 0.091), ('hans', 0.091), ('idiosyncratic', 0.088), ('confounded', 0.088), ('adolescent', 0.088), ('paper', 0.084), ('confidentiality', 0.081), ('causal', 0.081), ('sorts', 0.079), ('employed', 0.078), ('nicholas', 0.077), ('imagining', 0.077), ('anymore', 0.077), ('wrote', 0.076), ('unaware', 0.075), ('review', 0.075), ('restrictions', 0.074), ('behaviors', 0.073), ('exhibit', 0.072), ('brendan', 0.072), ('longitudinal', 0.072), ('obesity', 0.072), ('called', 0.072), ('property', 0.07), ('replications', 0.07), ('work', 0.069), ('propose', 0.068)]
simIndex simValue blogId blogTitle
same-blog 1 0.99999994 756 andrew gelman stats-2011-06-10-Christakis-Fowler update
Introduction: After I posted on Russ Lyons’s criticisms of the work of Nicholas Christakis and James Fowler’s work on social networks, several people emailed in with links to related articles. (Nobody wants to comment on the blog anymore; all I get is emails.) Here they are: Political scientists Hans Noel and Brendan Nyhan wrote a paper called “The ‘Unfriending’ Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence” in which they argue that the Christakis-Fowler results are subject to bias because of patterns in the time course of friendships. Statisticians Cosma Shalizi and AT wrote a paper called “Homophily and Contagion Are Generically Confounded in Observational Social Network Studies” arguing that analyses such as those of Christakis and Fowler cannot hope to disentangle different sorts of network effects. And Christakis and Fowler reply to Noel and Nyhan, Shalizi and Thomas, Lyons, and others in an article that begins: H
2 0.44136253 757 andrew gelman stats-2011-06-10-Controversy over the Christakis-Fowler findings on the contagion of obesity
Introduction: Nicholas Christakis and James Fowler are famous for finding that obesity is contagious. Their claims, which have been received with both respect and skepticism (perhaps we need a new word for this: “respecticism”?) are based on analysis of data from the Framingham heart study, a large longitudinal public-health study that happened to have some social network data (for the odd reason that each participant was asked to provide the name of a friend who could help the researchers locate them if they were to move away during the study period. The short story is that if your close contact became obese, you were likely to become obese also. The long story is a debate about the reliability of this finding (that is, can it be explained by measurement error and sampling variability) and its causal implications. This sort of study is in my wheelhouse, as it were, but I have never looked at the Christakis-Fowler work in detail. Thus, my previous and current comments are more along the line
3 0.36673856 1699 andrew gelman stats-2013-01-31-Fowlerpalooza!
Introduction: Russ Lyons points us to a discussion in Statistics in Medicine of the famous claims by Christakis and Fowler on the contagion of obesity etc. James O’Malley and Christakis and Fowler present the positive case. Andrew Thomas and Tyler VanderWeele present constructive criticism. Christakis and Fowler reply . Coincidentally, a couple weeks ago an epidemiologist was explaining to me the differences between the Framingham Heart Study and the Nurses Health Study and why Framingham got the postmenopausal supplement risks right while Nurses got it wrong. P.S. The journal issue also includes a comment on “A distribution-free test of constant mean in linear mixed effects models.” Wow! I had no idea people still did this sort of thing. How horrible. But I guess that’s what half-life is all about. These ideas last forever, they just become less and less relevant to people.
4 0.36257049 1412 andrew gelman stats-2012-07-10-More questions on the contagion of obesity, height, etc.
Introduction: AT discusses [link broken; see P.P.S. below] a new paper of his that casts doubt on the robustness of the controversial Christakis and Fowler papers. AT writes that he ran some simulations of contagion on social networks and found that (a) in a simple model assuming the contagion of the sort hypothesized by Christakis and Fowler, their procedure would indeed give the sorts of estimates they found in their papers, but (b) in another simple model assuming a different sort of contagion, the C&F; estimation would give indistinguishable estimates. Thus, if you believe AT’s simulation model, C&F;’s procedure cannot statistically distinguish between two sorts of contagion (directional and simultaneous). I have not looked at AT’s paper so I can’t fully comment, but I don’t fully understand his method for simulating network connections. AT uses what he calls a “rewiring” model. This makes sense: as time progresses, we make new friends and lose old ones—but I am confused by the details
Introduction: The other day, Nicholas Christakis wrote an article in the newspaper criticizing academic social science departments: The social sciences have stagnated. . . . This is not only boring but also counterproductive, constraining engagement with the scientific cutting edge and stifling the creation of new and useful knowledge. . . . I’m not suggesting that social scientists stop teaching and investigating classic topics like monopoly power, racial profiling and health inequality. But everyone knows that monopoly power is bad for markets, that people are racially biased and that illness is unequally distributed by social class. There are diminishing returns from the continuing study of many such topics. And repeatedly observing these phenomena does not help us fix them. I disagreed , saying that Christakis wasn’t giving social science research enough credit: I’m no economist so I can let others discuss the bit about “monopoly power is bad for markets.” I assume that the study by
7 0.14410682 1949 andrew gelman stats-2013-07-21-Defensive political science responds defensively to an attack on social science
8 0.1423388 706 andrew gelman stats-2011-05-11-The happiness gene: My bottom line (for now)
9 0.11309974 2268 andrew gelman stats-2014-03-26-New research journal on observational studies
10 0.10676501 1904 andrew gelman stats-2013-06-18-Job opening! Come work with us!
11 0.099406704 1630 andrew gelman stats-2012-12-18-Postdoc positions at Microsoft Research – NYC
12 0.098756194 728 andrew gelman stats-2011-05-24-A (not quite) grand unified theory of plagiarism, as applied to the Wegman case
13 0.09837994 202 andrew gelman stats-2010-08-12-Job openings in multilevel modeling in Bristol, England
14 0.095859066 1615 andrew gelman stats-2012-12-10-A defense of Tom Wolfe based on the impossibility of the law of small numbers in network structure
15 0.095350184 785 andrew gelman stats-2011-07-02-Experimental reasoning in social science
16 0.094497859 2245 andrew gelman stats-2014-03-12-More on publishing in journals
17 0.094111413 1878 andrew gelman stats-2013-05-31-How to fix the tabloids? Toward replicable social science research
18 0.09223181 1304 andrew gelman stats-2012-05-06-Picking on Stephen Wolfram
19 0.090840124 978 andrew gelman stats-2011-10-28-Cool job opening with brilliant researchers at Yahoo
20 0.089098468 2142 andrew gelman stats-2013-12-21-Chasing the noise
topicId topicWeight
[(0, 0.156), (1, -0.023), (2, -0.027), (3, -0.095), (4, -0.042), (5, 0.012), (6, -0.076), (7, -0.048), (8, -0.01), (9, 0.082), (10, 0.005), (11, -0.003), (12, 0.014), (13, -0.001), (14, -0.006), (15, 0.059), (16, -0.008), (17, -0.004), (18, -0.007), (19, -0.001), (20, -0.016), (21, -0.044), (22, -0.025), (23, 0.017), (24, 0.049), (25, 0.04), (26, 0.045), (27, -0.044), (28, 0.033), (29, -0.037), (30, -0.048), (31, -0.025), (32, -0.016), (33, -0.056), (34, 0.087), (35, 0.045), (36, -0.021), (37, 0.024), (38, 0.01), (39, -0.01), (40, 0.041), (41, 0.031), (42, -0.003), (43, -0.014), (44, -0.021), (45, -0.025), (46, -0.034), (47, -0.017), (48, -0.059), (49, -0.087)]
simIndex simValue blogId blogTitle
same-blog 1 0.95678812 756 andrew gelman stats-2011-06-10-Christakis-Fowler update
Introduction: After I posted on Russ Lyons’s criticisms of the work of Nicholas Christakis and James Fowler’s work on social networks, several people emailed in with links to related articles. (Nobody wants to comment on the blog anymore; all I get is emails.) Here they are: Political scientists Hans Noel and Brendan Nyhan wrote a paper called “The ‘Unfriending’ Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence” in which they argue that the Christakis-Fowler results are subject to bias because of patterns in the time course of friendships. Statisticians Cosma Shalizi and AT wrote a paper called “Homophily and Contagion Are Generically Confounded in Observational Social Network Studies” arguing that analyses such as those of Christakis and Fowler cannot hope to disentangle different sorts of network effects. And Christakis and Fowler reply to Noel and Nyhan, Shalizi and Thomas, Lyons, and others in an article that begins: H
Introduction: I’m sorry I don’t have any new zombie papers in time for Halloween. Instead I’d like to be a little monster by reproducing a mini-rant from this article on experimental reasoning in social science: I will restrict my discussion to social science examples. Social scientists are often tempted to illustrate their ideas with examples from medical research. When it comes to medicine, though, we are, with rare exceptions, at best ignorant laypersons (in my case, not even reaching that level), and it is my impression that by reaching for medical analogies we are implicitly trying to borrow some of the scientific and cultural authority of that field for our own purposes. Evidence-based medicine is the subject of a large literature of its own (see, for example, Lau, Ioannidis, and Schmid, 1998).
Introduction: The other day, Nicholas Christakis wrote an article in the newspaper criticizing academic social science departments: The social sciences have stagnated. . . . This is not only boring but also counterproductive, constraining engagement with the scientific cutting edge and stifling the creation of new and useful knowledge. . . . I’m not suggesting that social scientists stop teaching and investigating classic topics like monopoly power, racial profiling and health inequality. But everyone knows that monopoly power is bad for markets, that people are racially biased and that illness is unequally distributed by social class. There are diminishing returns from the continuing study of many such topics. And repeatedly observing these phenomena does not help us fix them. I disagreed , saying that Christakis wasn’t giving social science research enough credit: I’m no economist so I can let others discuss the bit about “monopoly power is bad for markets.” I assume that the study by
Introduction: Nicholas Christakis, a medical scientist perhaps best known for his controversial claim (see also here ), based on joint work with James Fowler, that obesity is contagious, writes : The social sciences have stagnated. They offer essentially the same set of academic departments and disciplines that they have for nearly 100 years: sociology, economics, anthropology, psychology and political science. This is not only boring but also counterproductive, constraining engagement with the scientific cutting edge and stifling the creation of new and useful knowledge. . . . I’m not suggesting that social scientists stop teaching and investigating classic topics like monopoly power, racial profiling and health inequality. But everyone knows that monopoly power is bad for markets, that people are racially biased and that illness is unequally distributed by social class. There are diminishing returns from the continuing study of many such topics. And repeatedly observing these phenomen
5 0.72317821 757 andrew gelman stats-2011-06-10-Controversy over the Christakis-Fowler findings on the contagion of obesity
Introduction: Nicholas Christakis and James Fowler are famous for finding that obesity is contagious. Their claims, which have been received with both respect and skepticism (perhaps we need a new word for this: “respecticism”?) are based on analysis of data from the Framingham heart study, a large longitudinal public-health study that happened to have some social network data (for the odd reason that each participant was asked to provide the name of a friend who could help the researchers locate them if they were to move away during the study period. The short story is that if your close contact became obese, you were likely to become obese also. The long story is a debate about the reliability of this finding (that is, can it be explained by measurement error and sampling variability) and its causal implications. This sort of study is in my wheelhouse, as it were, but I have never looked at the Christakis-Fowler work in detail. Thus, my previous and current comments are more along the line
6 0.72111022 382 andrew gelman stats-2010-10-30-“Presidential Election Outcomes Directly Influence Suicide Rates”
7 0.69572806 2361 andrew gelman stats-2014-06-06-Hurricanes vs. Himmicanes
8 0.6912148 1699 andrew gelman stats-2013-01-31-Fowlerpalooza!
9 0.67471159 785 andrew gelman stats-2011-07-02-Experimental reasoning in social science
10 0.66974622 32 andrew gelman stats-2010-05-14-Causal inference in economics
11 0.66758436 2220 andrew gelman stats-2014-02-22-Quickies
12 0.66687107 789 andrew gelman stats-2011-07-07-Descriptive statistics, causal inference, and story time
13 0.66200882 556 andrew gelman stats-2011-02-04-Patterns
14 0.65675294 1671 andrew gelman stats-2013-01-13-Preregistration of Studies and Mock Reports
15 0.65238148 2185 andrew gelman stats-2014-01-25-Xihong Lin on sparsity and density
16 0.64096832 1833 andrew gelman stats-2013-04-30-“Tragedy of the science-communication commons”
17 0.63694531 1128 andrew gelman stats-2012-01-19-Sharon Begley: Worse than Stephen Jay Gould?
19 0.63488913 145 andrew gelman stats-2010-07-13-Statistical controversy regarding human rights violations in Colomnbia
20 0.63220334 978 andrew gelman stats-2011-10-28-Cool job opening with brilliant researchers at Yahoo
topicId topicWeight
[(16, 0.083), (24, 0.046), (31, 0.011), (53, 0.024), (99, 0.703)]
simIndex simValue blogId blogTitle
same-blog 1 0.99930298 756 andrew gelman stats-2011-06-10-Christakis-Fowler update
Introduction: After I posted on Russ Lyons’s criticisms of the work of Nicholas Christakis and James Fowler’s work on social networks, several people emailed in with links to related articles. (Nobody wants to comment on the blog anymore; all I get is emails.) Here they are: Political scientists Hans Noel and Brendan Nyhan wrote a paper called “The ‘Unfriending’ Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence” in which they argue that the Christakis-Fowler results are subject to bias because of patterns in the time course of friendships. Statisticians Cosma Shalizi and AT wrote a paper called “Homophily and Contagion Are Generically Confounded in Observational Social Network Studies” arguing that analyses such as those of Christakis and Fowler cannot hope to disentangle different sorts of network effects. And Christakis and Fowler reply to Noel and Nyhan, Shalizi and Thomas, Lyons, and others in an article that begins: H
2 0.99805504 1288 andrew gelman stats-2012-04-29-Clueless Americans think they’ll never get sick
Introduction: Cassie Murdoch points to a report from a corporate survey: Sixty-two percent of U.S. employees say it’s not likely they or a family member will be diagnosed with a serious illness like cancer, a survey indicates. The Aflac WorkForces Report, a survey of nearly 1,900 benefits decision-makers and more than 6,100 U.S. workers, also indicated 55 percent said they were not very or not at all likely to be diagnosed with a chronic illness, such as heart disease or diabetes. Here are some actual statistics: The American Cancer Society, Cancer Facts & Figures 2012, said 1-in-3 women and 1-in-2 men will be diagnosed with cancer at some point in their lives, and the National Safety Council, Injury Facts 2011 edition, says more than 38.9 million injuries occur in a year requiring medical treatment. The American Heart Association, Heart Disease & Stroke Statistics 2012, said 1-in-6 U.S. deaths were caused by coronary heart disease, Tillman said. And some details on the survey:
3 0.99770844 180 andrew gelman stats-2010-08-03-Climate Change News
Introduction: I. State of the Climate report The National Oceanic and Atmospheric Administration recently released their “State of the Climate Report” for 2009 . The report has chapters discussing global climate (temperatures, water vapor, cloudiness, alpine glaciers,…); oceans (ocean heat content, sea level, sea surface temperatures, etc.); the arctic (sea ice extent, permafrost, vegetation, and so on); Antarctica (weather observations, sea ice extent,…), and regional climates. NOAA also provides a nice page that lets you display any of 11 relevant time-series datasets (land-surface air temperature, sea level, ocean heat content, September arctic sea-ice extent, sea-surface temperature, northern hemisphere snow cover, specific humidity, glacier mass balance, marine air temperature, tropospheric temperature, and stratospheric temperature). Each of the plots overlays data from several databases (not necessarily indepenedent of each other), and you can select which ones to include or leave
4 0.99718964 740 andrew gelman stats-2011-06-01-The “cushy life” of a University of Illinois sociology professor
Introduction: Xian points me to an article by retired college professor David Rubinstein who argues that college professors are underworked and overpaid: After 34 years of teaching sociology at the University of Illinois at Chicago, I [Rubinstein] recently retired at age 64 at 80 percent of my pay for life. . . . But that’s not all: There’s a generous health insurance plan, a guaranteed 3 percent annual cost of living increase, and a few other perquisites. . . . I was also offered the opportunity to teach as an emeritus for three years, receiving $8,000 per course . . . which works out to over $200 an hour. . . . You will perhaps not be surprised to hear that I had two immediate and opposite reactions to this: 1. Hey–somebody wants to cut professors’ salaries. Stop him! 2. Hey–this guy’s making big bucks and doesn’t do any work–that’s not fair! (I went online to find David Rubinstein’s salary but it didn’t appear in the database. So I did the next best thing and looked up the sala
5 0.99568361 761 andrew gelman stats-2011-06-13-A survey’s not a survey if they don’t tell you how they did it
Introduction: Since we’re on the topic of nonreplicable research . . . see here (link from here ) for a story of a survey that’s so bad that the people who did it won’t say how they did it. I know too many cases where people screwed up in a survey when they were actually trying to get the right answer, for me to trust any report of a survey that doesn’t say what they did. I’m reminded of this survey which may well have been based on a sample of size 6 (again, the people who did it refused to release any description of methodology).
6 0.99563646 772 andrew gelman stats-2011-06-17-Graphical tools for understanding multilevel models
7 0.99546272 1813 andrew gelman stats-2013-04-19-Grad students: Participate in an online survey on statistics education
9 0.99464649 521 andrew gelman stats-2011-01-17-“the Tea Party’s ire, directed at Democrats and Republicans alike”
10 0.99428838 1434 andrew gelman stats-2012-07-29-FindTheData.org
11 0.99421728 174 andrew gelman stats-2010-08-01-Literature and life
12 0.99402261 1483 andrew gelman stats-2012-09-04-“Bestselling Author Caught Posting Positive Reviews of His Own Work on Amazon”
13 0.99375778 1315 andrew gelman stats-2012-05-12-Question 2 of my final exam for Design and Analysis of Sample Surveys
14 0.99367446 589 andrew gelman stats-2011-02-24-On summarizing a noisy scatterplot with a single comparison of two points
15 0.99364537 860 andrew gelman stats-2011-08-18-Trolls!
16 0.99324822 809 andrew gelman stats-2011-07-19-“One of the easiest ways to differentiate an economist from almost anyone else in society”
17 0.99302185 638 andrew gelman stats-2011-03-30-More on the correlation between statistical and political ideology
19 0.99237531 1431 andrew gelman stats-2012-07-27-Overfitting
20 0.9923079 1425 andrew gelman stats-2012-07-23-Examples of the use of hierarchical modeling to generalize to new settings