andrew_gelman_stats andrew_gelman_stats-2014 knowledge-graph by maker-knowledge-mining
Introduction: EJ points me to this new techno-thriller . Based on the sentence quoted above, I don’t see it selling lots of copies. It reads like a really boring Raymond Chandler. I still think these two movie ideas would be a better sell.
2 andrew gelman stats-2014-06-11-Bayes in the research conversation
Introduction: Charlie Williams writes: As I get interested in Bayesian approaches to statistics, I have one question I wondered if you would find interesting to address at some point on the blog. What does Bayesian work look like in action across a field? From experience, I have some feeling for how ongoing debates evolve (or not) with subsequent studies in response to earlier findings. I wonder if you know how this happens in practice when multiple researchers are using Bayesian approaches. How much are previous findings built into priors? How much advance comes from model improvement? And in a social science field where self-selection and self-interest play a role, how are improved “treatment” effects incorporated and evaluated? I thought you might know of a field where actual back and forth has been carried out mostly in the context of Bayesian analysis or inference, and I thought it would be interesting to take a look at an example as I think about my own field. My reply: I’ve seen Ba
3 andrew gelman stats-2014-06-10-Spring forward, fall back, drop dead?
Introduction: Antonio Rinaldi points me to a press release describing a recent paper by Amneet Sandhu, Milan Seth, and Hitinder Gurm, where I got the above graphs (sorry about the resolution, that’s the best I could do). Here’s the press release: Data from the largest study of its kind in the U.S. reveal a 25 percent jump in the number of heart attacks occurring the Monday after we “spring forward” compared to other Mondays during the year – a trend that remained even after accounting for seasonal variations in these events. But the study showed the opposite effect is also true. Researchers found a 21 percent drop in the number of heart attacks on the Tuesday after returning to standard time in the fall when we gain an hour back. Rinaldi thinks: “On Tuesday? No multiple comparisons here???” The press release continues: “What’s interesting is that the total number of heart attacks didn’t change the week after daylight saving time,” said Amneet Sandhu, M.D., cardiology fellow, Univer
4 andrew gelman stats-2014-06-09-On deck this week
Introduction: Mon: I hate polynomials Tues: Spring forward, fall back, drop dead? Wed: Bayes in the research conversation Thurs: The health policy innovation center: how best to move from pilot studies to large-scale practice? Fri: Stroopy names Sat: He’s not so great in math but wants to do statistics and machine learning Sun: Comparing the full model to the partial model
5 andrew gelman stats-2014-06-09-I hate polynomials
Introduction: A recent discussion with Mark Palko [scroll down to the comments at this link ] reminds me that I think that polynomials are way way overrated, and I think a lot of damage has arisen from the old-time approach of introducing polynomial functions as a canonical example of linear regressions ( for example ). There are very few settings I can think of where it makes sense to fit a general polynomial of degree higher than 2. I think that millions of students have been brainwashed into thinking of these as the canonical functions and that this has caused endless trouble later on. I’m not sure how I’d change the high school math curriculum to deal with this, but I do think it’s an issue.
6 andrew gelman stats-2014-06-08-Regression and causality and variable ordering
Introduction: Bill Harris wrote in with a question: David Hogg points out in one of his general articles on data modeling that regression assumptions require one to put the variable with the highest variance in the ‘y’ position and the variable you know best (lowest variance) in the ‘x’ position. As he points out, others speak of independent and dependent variables, as if causality determined the form of a regression formula. In a quick scan of ARM and BDA, I don’t see clear advice, but I do see the use of ‘independent’ and ‘dependent.’ I recently did a model over data in which we know the ‘effect’ pretty well (we measure it), while we know the ’cause’ less well (it’s estimated by people who only need to get it approximately correct). A model of the form ’cause ~ effect’ fit visually much better than one of the form ‘effect ~ cause’, but interpreting it seems challenging. For a simplistic example, let the effect be energy use in a building for cooling (E), and let the cause be outdoor ai
7 andrew gelman stats-2014-06-07-“Does researching casual marijuana use cause brain abnormalities?”
Introduction: David Austin points me to a wonderfully-titled post by Lior Pachter criticizing a recent paper on the purported effects of cannabis use. Not the paper criticized here . Someone should send this all to David Brooks. I’ve heard he’s interested in the latest scientific findings, and I know he’s interested in marijuana.
8 andrew gelman stats-2014-06-06-Statistically savvy journalism
Introduction: Roy Mendelssohn points me to this excellent bit of statistics reporting by Matt Novak. I have no comment, I just think it’s good to see this sort of high-quality Felix Salmon-style statistically savvy journalism.
9 andrew gelman stats-2014-06-06-Hurricanes vs. Himmicanes
Introduction: The story’s on the sister blog and I quote liberally from Jeremy Freese, who wrote : The authors have issued a statement that argues against some criticisms of their study that others have offered. These are irrelevant to the above observations, as I [Freese] am taking everything about the measurement and model specification at their word–my starting point is the model that fully replicates the analyses that they themselves published. A qualification is that one of their comments is that they deny they are making any claims about the importance of other factors that kill people in hurricanes. But they are. If you claim that 27 out of the 42 deaths in Hurricane Eloise would have been prevented if it was named Hurricane Charley, that is indeed a claim that diminishes the potential importance of other causes of deaths in that hurricane. Freese also raises an important general issue in science communication: The authors’ university issued a press release with a dramatic prese
Introduction: Andrew Tanentzap, William Lee, Adrian Monks, Kate Ladley, Peter Johnson, Geoffrey Rogers, Joy Comrie, Dean Clarke, and Ella Hayman write : We tested a multivariate hypothesis about the causal mechanisms underlying plant invasions in an ephemeral wetland in South Island, New Zealand to inform management of this biodiverse but globally imperilled habitat. . . . We found that invasion by non-native plants was lowest in sites where the physical disturbance caused by flooding was both intense and frequent. . . . only species adapted to the dominant disturbance regimes at a site may become successful invaders. Their keywords are: causal networks; community dynamics; functional traits, invasive species, kettlehole; megafauna; rabbits; restoration; turf plants But here’s the part that I like best: We fitted all our models within a hierarchical Bayesian framework using . . . STAN v.1.3 (Stan Development Team 2012) from R v.2.15 (R Development Core Team 2012).
11 andrew gelman stats-2014-06-04-All the Assumptions That Are My Life
Introduction: Statisticians take tours in other people’s data. All methods of statistical inference rest on statistical models. Experiments typically have problems with compliance, measurement error, generalizability to the real world, and representativeness of the sample. Surveys typically have problems of undercoverage, nonresponse, and measurement error. Real surveys are done to learn about the general population. But real surveys are not random samples. For another example, consider educational tests: what are they exactly measuring? Nobody knows. Medical research: even if it’s a randomized experiment, the participants in the study won’t be a random sample from the population for whom you’d recommend treatment. You don’t need random sampling to generalize the results of a medical experiment to the general population but you need some substantive theory to make the assumption that effects in your nonrepresentative sample of people will be similar to effects in the population of interest. Ve
Introduction: Please answer the above question before reading on . . . I’m curious after reading Leif Nelson’s report that, based on research with Minah Jung, approximately 42% of the people they surveyed said they bought laundry detergent on their most recent trip to the store. I’m stunned that the number is so high. 42%??? That’s almost half the time. If we bought laundry detergent half the time we went to the store, our apartment would be stacked so full with the stuff, we wouldn’t be able to enter the door. I think we buy laundry detergent . . . ummm, how often? There are 40 of those little laundry packets in the box, we do laundry once a day, sometimes twice, let’s say 10 times a week, so this means we buy detergent about once every 4 weeks. We go to the store, hmmm, about once a day, let’s say 5 times a week to put our guess on the conservative side. So, 20 trips to the store for each purchase of detergent, that’s 5% of the time. Compared to us, lots of people must (a) go to
13 andrew gelman stats-2014-06-02-Why we hate stepwise regression
Introduction: Haynes Goddard writes: I have been slowly working my way through the grad program in stats here, and the latest course was a biostats course on categorical and survival analysis. I noticed in the semi-parametric and parametric material (Wang and Lee is the text) that they use stepwise regression a lot. I learned in econometrics that stepwise is poor practice, as it defaults to the “theory of the regression line”, that is no theory at all, just the variation in the data. I don’t find the topic on your blog, and wonder if you have addressed the issue. My reply: Stepwise regression is one of these things, like outlier detection and pie charts, which appear to be popular among non-statisticans but are considered by statisticians to be a bit of a joke. For example, Jennifer and I don’t mention stepwise regression in our book, not even once. To address the issue more directly: the motivation behind stepwise regression is that you have a lot of potential predictors but not e
14 andrew gelman stats-2014-06-02-On deck this week
Introduction: Mon: Why we hate stepwise regression Tues: Did you buy laundry detergent on their most recent trip to the store? Also comments on scientific publication and yet another suggestion to do a study that allows within-person comparisons Wed: All the Assumptions That Are My Life Thurs: Identifying pathways for managing multiple disturbances to limit plant invasions Fri: Statistically savvy journalism Sat: “Does researching casual marijuana use cause brain abnormalities?” Sun: Regression and causality and variable ordering
Introduction: Jessica Tracy and Alec Beall, authors of that paper that claimed that women at peak fertility were more likely to wear red or pink shirts (see further discussion here and here ), and then a later paper that claimed that this happens in some weather but not others, just informed me that they have posted a note in disagreement with an paper by Eric Loken and myself. Our paper is unpublished, but I do have the megaphone of this blog, and Tracy and Beall do not, so I think it’s only fair to link to their note right away. I’ll quote from their note (but if you’re interested, please follow the link and read the whole thing ) and then give some background and my own reaction. Tracy and Beall write: Although Gelman and Loken are using our work as an example of a broader problem that pervades the field–a problem we generally agree about–we are concerned that readers will take their speculations about our methods and analyses as factual claims about our scientific integrity. Fu
16 andrew gelman stats-2014-05-30-Mmm, statistical significance . . . Evilicious!
Introduction: Just in case you didn’t check Retraction Watch yet today , Carolyn Johnson reports: The committee painstakingly reconstructed the process of data analysis and determined that Hauser had changed values, causing the result to be statistically significant, an important criterion showing that findings are probably not due to chance. As the man said : His resignation is a serious loss for Harvard, and given the nature of the attack on him, for science generally. As a statistician, I don’t mind if someone is attacked because of cheating with data. Johnson concludes her news article in a pleasantly balanced way: The committee said it carefully considered Hauser’s allegation that people in his laboratory conspired against him, due to academic rivalry and disgruntlement, but did not find evidence to support the idea. The committee also acknowledged that many of Hauser’s overall findings about the cognitive abilities of animals may stand. His results that showed that animals
17 andrew gelman stats-2014-05-30-I posted this as a comment on a sociology blog
Introduction: I discussed two problems: 1. An artificial scarcity applied to journal publication, a scarcity which I believe is being enforced based on a monetary principle of not wanting to reduce the value of publication. The problem is that journals don’t just spread information and improve communication, they also represent chits for hiring and promotion. I’d prefer to separate these two aspects of publication. To keep these functions tied together seems to me like a terrible mistake. It would be as if, instead of using dollar bills as currency, we were to just use paper , and then if the government kept paper artificially scarce to retain the value of money, so that we were reduced to scratching notes to each other on walls and tables. 2. The discontinuous way in which unpublished papers and submissions to journals are taken as highly suspect and requiring a strong justification of all methods and assumptions, but once a paper becomes published its conclusions are taken as true unless
18 andrew gelman stats-2014-05-29-When you believe in things that you don’t understand
Introduction: Rolf Zwaan gives an excellent discussion of how superstition can arise and perpetuate itself: A social-behavioral priming experiment is like rolling a 20-sided die, an icosahedron. If you roll the die a number of times, 20 will turn up at some point. Bingo! You have a significant effect. In fact, given what we now know about questionable and not so questionable research practices, it is fair to assume that the researchers are actually rolling with a 20-sided die where maybe as many as six sides have a 20 on them. So the chances of rolling a 20 are quite high. Once the researchers have rolled a 20, their next interpretive move is to consider the circumstances that happened to coincide with rolling the die instrumental in producing the 20. The only problem is that they don’t know what those circumstances were. Was it the physical condition of the roller? Was it the weather? Was it the time of day? Was it the color of the roller’s sweater? Indeed, we’ve been told first that it
19 andrew gelman stats-2014-05-28-Bayesian nonparametric weighted sampling inference
Introduction: Yajuan Si, Natesh Pillai, and I write : It has historically been a challenge to perform Bayesian inference in a design-based survey context. The present paper develops a Bayesian model for sampling inference using inverse-probability weights. We use a hierarchical approach in which we model the distribution of the weights of the nonsampled units in the population and simultaneously include them as predictors in a nonparametric Gaussian process regression. We use simulation studies to evaluate the performance of our procedure and compare it to the classical design-based estimator. We apply our method to the Fragile Family Child Wellbeing Study. Our studies find the Bayesian nonparametric finite population estimator to be more robust than the classical design-based estimator without loss in efficiency. More work needs to be done for this to be a general practical tool—in particular, in the setup of this paper you only have survey weights and no direct poststratification variab
Introduction: We had a discussion the other day of a paper, “The Economic Effects of Climate Change,” by economist Richard Tol. The paper came to my attention after I saw a notice from Adam Marcus that it was recently revised because of data errors. But after looking at the paper more carefully, I see a bunch of other problems that, to me, make the whole analysis close to useless as it stands. I think this is worth discussing because the paper has been somewhat influential (so far cited 328 times, according to Google Scholar) and has even been cited in the popular press as evidence that “Climate change has done more good than harm so far and is likely to continue doing so for most of this century . . . There are many likely effects of climate change: positive and negative, economic and ecological, humanitarian and financial. And if you aggregate them all, the overall effect is positive today — and likely to stay positive until around 2080. That was the conclusion of Professor Richard Tol
21 andrew gelman stats-2014-05-26-WAIC and cross-validation in Stan!
22 andrew gelman stats-2014-05-26-On deck this week
23 andrew gelman stats-2014-05-25-Why I decided not to be a physicist
24 andrew gelman stats-2014-05-24-Buzzfeed, Porn, Kansas…That Can’t Be Good
25 andrew gelman stats-2014-05-24-An interesting mosaic of a data programming course
27 andrew gelman stats-2014-05-22-Big Data needs Big Model
28 andrew gelman stats-2014-05-21-Models with constraints
29 andrew gelman stats-2014-05-20-plus ça change, plus c’est la même chose
31 andrew gelman stats-2014-05-19-On deck this week
32 andrew gelman stats-2014-05-19-My short career as a Freud expert
33 andrew gelman stats-2014-05-18-Never back down: The culture of poverty and the culture of journalism
36 andrew gelman stats-2014-05-14-“The subtle funk of just a little poultry offal”
37 andrew gelman stats-2014-05-13-Personally, I’d rather go with Teragram
38 andrew gelman stats-2014-05-12-“The results (not shown) . . .”
39 andrew gelman stats-2014-05-12-On deck this week
40 andrew gelman stats-2014-05-12-Historical Arc of Universities
41 andrew gelman stats-2014-05-11-“What should you talk about?”
43 andrew gelman stats-2014-05-09-Nicholas Wade and the paradox of racism
45 andrew gelman stats-2014-05-07-Stan users meetup next week
46 andrew gelman stats-2014-05-07-Once more on nonparametric measures of mutual information
47 andrew gelman stats-2014-05-07-Cause he thinks he’s so-phisticated
48 andrew gelman stats-2014-05-06-Priors I don’t believe
49 andrew gelman stats-2014-05-05-On deck this week
50 andrew gelman stats-2014-05-05-On deck this month
51 andrew gelman stats-2014-05-05-Can we make better graphs of global temperature history?
52 andrew gelman stats-2014-05-04-Stan (& JAGS) Tutorial on Linear Mixed Models
53 andrew gelman stats-2014-05-04-Honored oldsters write about statistics
55 andrew gelman stats-2014-05-02-Discovering general multidimensional associations
57 andrew gelman stats-2014-04-30-Seth Roberts
59 andrew gelman stats-2014-04-29-Bayesian Uncertainty Quantification for Differential Equations!
60 andrew gelman stats-2014-04-28-On deck this week
61 andrew gelman stats-2014-04-28-Crowdstorming a dataset
62 andrew gelman stats-2014-04-27-White stripes and dead armadillos
63 andrew gelman stats-2014-04-27-Big Data…Big Deal? Maybe, if Used with Caution.
66 andrew gelman stats-2014-04-24-An open site for researchers to post and share papers
68 andrew gelman stats-2014-04-23-A short questionnaire regarding the subjective assessment of evidence
69 andrew gelman stats-2014-04-22-Ticket to Baaaaarf
70 andrew gelman stats-2014-04-21-Ticket to Baaaath
71 andrew gelman stats-2014-04-21-Stan Model of the Week: Hierarchical Modeling of Supernovas
72 andrew gelman stats-2014-04-21-On deck this week
73 andrew gelman stats-2014-04-20-Fooled by randomness
74 andrew gelman stats-2014-04-19-Index or indicator variables
75 andrew gelman stats-2014-04-18-One-tailed or two-tailed?
78 andrew gelman stats-2014-04-15-When you believe in things that you don’t understand
79 andrew gelman stats-2014-04-14-Transitioning to Stan
80 andrew gelman stats-2014-04-14-On deck this week
81 andrew gelman stats-2014-04-11-“More research from the lunatic fringe”
83 andrew gelman stats-2014-04-09-Advice: positive-sum, zero-sum, or negative-sum
84 andrew gelman stats-2014-04-08-Understanding Simpson’s paradox using a graph
85 andrew gelman stats-2014-04-07-On deck this week
87 andrew gelman stats-2014-04-06-An old discussion of food deserts
88 andrew gelman stats-2014-04-05-Bizarre academic spam
89 andrew gelman stats-2014-04-04-The Notorious N.H.S.T. presents: Mo P-values Mo Problems
91 andrew gelman stats-2014-04-02-Am I too negative?
92 andrew gelman stats-2014-04-01-Association for Psychological Science announces a new journal
93 andrew gelman stats-2014-03-31-The most-cited statistics papers ever
94 andrew gelman stats-2014-03-31-On deck this week
95 andrew gelman stats-2014-03-31-Just gave a talk
98 andrew gelman stats-2014-03-29-I agree with this comment
99 andrew gelman stats-2014-03-28-What happened to the world we knew?
100 andrew gelman stats-2014-03-28-Creating a Lenin-style democracy
101 andrew gelman stats-2014-03-27-Beyond the Valley of the Trolls
102 andrew gelman stats-2014-03-26-New research journal on observational studies
103 andrew gelman stats-2014-03-26-Is a steal really worth 9 points?
104 andrew gelman stats-2014-03-25-A statistical graphics course and statistical graphics advice
105 andrew gelman stats-2014-03-24-On deck this week
106 andrew gelman stats-2014-03-24-On deck this month
108 andrew gelman stats-2014-03-23-Win probabilities during a sporting event
109 andrew gelman stats-2014-03-23-Greg Mankiw’s utility function
110 andrew gelman stats-2014-03-22-Postdoc at Rennes on multilevel missing data imputation
111 andrew gelman stats-2014-03-22-Picking pennies in front of a steamroller: A parable comes to life
112 andrew gelman stats-2014-03-21-Random matrices in the news
113 andrew gelman stats-2014-03-20-The candy weighing demonstration, or, the unwisdom of crowds
115 andrew gelman stats-2014-03-19-How Americans vote
117 andrew gelman stats-2014-03-17-On deck this week: Revisitings
118 andrew gelman stats-2014-03-17-Ma conférence demain (mardi) à l’École Polytechnique
120 andrew gelman stats-2014-03-16-“I have no idea who Catalina Garcia is, but she makes a decent ruler”
121 andrew gelman stats-2014-03-15-Recently in the sister blog
122 andrew gelman stats-2014-03-15-Problematic interpretations of confidence intervals
123 andrew gelman stats-2014-03-14-The maximal information coefficient
124 andrew gelman stats-2014-03-13-An Economist’s Guide to Visualizing Data
125 andrew gelman stats-2014-03-12-More on publishing in journals
126 andrew gelman stats-2014-03-11-What if I were to stop publishing in journals?
127 andrew gelman stats-2014-03-11-The myth of the myth of the myth of the hot hand
128 andrew gelman stats-2014-03-10-Stan Model of the Week: PK Calculation of IV and Oral Dosing
129 andrew gelman stats-2014-03-10-Preregistration: what’s in it for you?
130 andrew gelman stats-2014-03-10-On deck this week: Things people sent me
131 andrew gelman stats-2014-03-09-Reviewing the peer review process?
132 andrew gelman stats-2014-03-09-Hipmunk worked
133 andrew gelman stats-2014-03-08-Disagreeing to disagree
134 andrew gelman stats-2014-03-07-Selection bias in the reporting of shaky research
136 andrew gelman stats-2014-03-05-Plagiarism, Arizona style
137 andrew gelman stats-2014-03-04-Literal vs. rhetorical
138 andrew gelman stats-2014-03-03-What is the appropriate time scale for blogging—the day or the week?
139 andrew gelman stats-2014-03-03-Running into a Stan Reference by Accident
141 andrew gelman stats-2014-02-28-God-leaf-tree
142 andrew gelman stats-2014-02-28-Combining two of my interests
143 andrew gelman stats-2014-02-27-“What Can we Learn from the Many Labs Replication Project?”
145 andrew gelman stats-2014-02-26-A good comment on one of my papers
147 andrew gelman stats-2014-02-24-“Edlin’s rule” for routinely scaling down published estimates
148 andrew gelman stats-2014-02-24-On deck this week
149 andrew gelman stats-2014-02-23-Postdoc with Huffpost Pollster to do Bayesian poll tracking
150 andrew gelman stats-2014-02-22-Quickies
154 andrew gelman stats-2014-02-18-Florida backlash
156 andrew gelman stats-2014-02-17-On deck this week
157 andrew gelman stats-2014-02-16-There’s no need for you to read this one
158 andrew gelman stats-2014-02-15-Mary, Mary, why ya buggin
160 andrew gelman stats-2014-02-13-Stopping rules and Bayesian analysis
161 andrew gelman stats-2014-02-13-CmdStan, RStan, PyStan v2.2.0
162 andrew gelman stats-2014-02-12-How to think about “identifiability” in Bayesian inference?
163 andrew gelman stats-2014-02-11-My talks in Bristol this Wed and London this Thurs
164 andrew gelman stats-2014-02-10-On deck this week
165 andrew gelman stats-2014-02-10-More on US health care overkill
166 andrew gelman stats-2014-02-09-Keli Liu and Xiao-Li Meng on Simpson’s paradox
167 andrew gelman stats-2014-02-08-“Guys who do more housework get less sex”
168 andrew gelman stats-2014-02-07-Outrage of the week
170 andrew gelman stats-2014-02-05-Prior distribution for a predicted probability
171 andrew gelman stats-2014-02-04-Widening the goalposts in medical trials
172 andrew gelman stats-2014-02-04-Special discount on Stan! $999 cheaper than Revolution R!
173 andrew gelman stats-2014-02-04-Peabody here.
175 andrew gelman stats-2014-02-02-Microfoundations of macroeconomics
176 andrew gelman stats-2014-02-01-Recently in the sister blog
178 andrew gelman stats-2014-01-30-History is too important to be left to the history professors, Part 2
180 andrew gelman stats-2014-01-29-Stupid R Tricks: Random Scope
181 andrew gelman stats-2014-01-28-History is too important to be left to the history professors
182 andrew gelman stats-2014-01-27-“Disappointed with your results? Boost your scientific paper”
183 andrew gelman stats-2014-01-26-Twitter sucks, and people are gullible as f…
184 andrew gelman stats-2014-01-26-Infoviz on top of stat graphic on top of spreadsheet
185 andrew gelman stats-2014-01-25-Xihong Lin on sparsity and density
186 andrew gelman stats-2014-01-24-Parables vs. stories
187 andrew gelman stats-2014-01-23-Discussion on preregistration of research studies
189 andrew gelman stats-2014-01-21-The Commissar for Traffic presents the latest Five-Year Plan
191 andrew gelman stats-2014-01-20-The AAA Tranche of Subprime Science
192 andrew gelman stats-2014-01-20-Mailing List Degree-of-Difficulty Difficulty
193 andrew gelman stats-2014-01-19-“The British amateur who debunked the mathematics of happiness”
194 andrew gelman stats-2014-01-19-Transformations for non-normal data
195 andrew gelman stats-2014-01-18-A course in sample surveys for political science
198 andrew gelman stats-2014-01-14-Advice on writing research articles
202 andrew gelman stats-2014-01-12-Things that I like that almost nobody else is interested in
204 andrew gelman stats-2014-01-10-3 years out of date on the whole Dennis the dentist thing!
206 andrew gelman stats-2014-01-09-Hermann Goering and Jane Jacobs, together at last!
207 andrew gelman stats-2014-01-08-How to display multinominal logit results graphically?
208 andrew gelman stats-2014-01-08-Belief aggregation
209 andrew gelman stats-2014-01-07-My recent debugging experience
210 andrew gelman stats-2014-01-06-Spam names
212 andrew gelman stats-2014-01-03-Booze: Been There. Done That.
213 andrew gelman stats-2014-01-02-2013