andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-426 knowledge-graph by maker-knowledge-mining
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Introduction: The deadline for this year’s Earth Institute postdocs is 1 Dec, so it’s time to apply right away ! It’s a highly competitive interdisciplinary program, and we’ve had some statisticians in the past. We’re particularly interested in statisticians who have research interests in development and public health. It’s fine–not just fine, but ideal–if you are interested in statistical methods also.
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Introduction: The deadline for this year’s Earth Institute postdocs is 1 Dec, so it’s time to apply right away ! It’s a highly competitive interdisciplinary program, and we’ve had some statisticians in the past. We’re particularly interested in statisticians who have research interests in development and public health. It’s fine–not just fine, but ideal–if you are interested in statistical methods also.
2 0.48519921 971 andrew gelman stats-2011-10-25-Apply now for Earth Institute postdoctoral fellowships at Columbia University
Introduction: The economy isn’t going so well, but there are some interesting possibilities here at Columbia University. One such option that you should be thinking about is the Earth Institute Fellowship , which pays well, includes a research stipend, and puts you in an exciting interdisciplinary community of faculty and postdoctoral researchers. The Earth Institute at Columbia brings in several postdocs each year–it’s a two-year gig–and some of them have been statisticians (recently, Kenny Shirley and Leontine Alkema). We’re particularly interested in statisticians who have research interests in development and public health. It’s fine–not just fine, but ideal–if you are interested in statistical methods also. The EI postdoc can be a place to do interesting work and begin a research career. If you’re a statistician who’s interested in this fellowship, feel free to contact me directly–you have to apply to the Earth Institute directly (see link above), but I’m happy to give you advice about
Introduction: (1) Hop the Q-Train ! That is, the Columbia/NYU Quantitative Training Program, funded by the Institute of Education Sciences to create a cohort of postdoctoral scholars both to develop the new statistical methods required to meet future research challenges and to effectively train and consult with other education researchers. You’ll be working with Jennifer Hill, Marc Scott, and me on our exciting research projects, some of which are here ! Candidates must be United States citizens or permanent residents. For best consideration applications must be submitted before 15 Nov 2012. Please direct administrative inquiries to Jonathan Winters at jonathan.winters@nyu.edu and substantive inquiries to Jennifer or me. (2) The Earth Institute Postdoctoral Fellows program ! Every year a select group of recent Ph.D.s in a variety of fields come to the Earth Institute for this two-year research fellowship. I’d love to see more statisticians applying. To apply, candidates must compl
4 0.15991428 1275 andrew gelman stats-2012-04-22-Please stop me before I barf again
Introduction: Pointing to some horrible graphs, Kaiser writes, “The Earth Institute needs a graphics adviser.” I agree. The graphs are corporate standard, neither pretty or innovative enough to qualify as infographics, not informational enough to be good statistical data displays. Some examples include the above exploding pie chart, which, as Kaiser notes, is not merely ugly and ridiculously difficult to read (given that it is conveying only nine data points) but also invites suspicion of its numbers, and pages and pages of graphs that could be better compressed into a compact displays (see pages 25-65 of the report). Yes, this is all better than tables of numbers, but I don’t see that much thought went into displaying patterns of information or telling a story. It’s more graph-as-data-dump. To be fair, the report does have some a clean scatterplot (on page 65). But, overall, the graphs are not well-integrated with the messages in the text. I feel a little bit bad about this, beca
5 0.14486483 147 andrew gelman stats-2010-07-15-Quote of the day: statisticians and defaults
Introduction: On statisticians and statistical software: Statisticians are particularly sensitive to default settings, which makes sense considering that statistics is, in many ways, a science based on defaults. What is a “statistical method” if not a recommended default analysis, backed up by some combination of theory and experience?
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Introduction: The deadline for this year’s Earth Institute postdocs is 1 Dec, so it’s time to apply right away ! It’s a highly competitive interdisciplinary program, and we’ve had some statisticians in the past. We’re particularly interested in statisticians who have research interests in development and public health. It’s fine–not just fine, but ideal–if you are interested in statistical methods also.
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Introduction: The economy isn’t going so well, but there are some interesting possibilities here at Columbia University. One such option that you should be thinking about is the Earth Institute Fellowship , which pays well, includes a research stipend, and puts you in an exciting interdisciplinary community of faculty and postdoctoral researchers. The Earth Institute at Columbia brings in several postdocs each year–it’s a two-year gig–and some of them have been statisticians (recently, Kenny Shirley and Leontine Alkema). We’re particularly interested in statisticians who have research interests in development and public health. It’s fine–not just fine, but ideal–if you are interested in statistical methods also. The EI postdoc can be a place to do interesting work and begin a research career. If you’re a statistician who’s interested in this fellowship, feel free to contact me directly–you have to apply to the Earth Institute directly (see link above), but I’m happy to give you advice about
Introduction: (1) Hop the Q-Train ! That is, the Columbia/NYU Quantitative Training Program, funded by the Institute of Education Sciences to create a cohort of postdoctoral scholars both to develop the new statistical methods required to meet future research challenges and to effectively train and consult with other education researchers. You’ll be working with Jennifer Hill, Marc Scott, and me on our exciting research projects, some of which are here ! Candidates must be United States citizens or permanent residents. For best consideration applications must be submitted before 15 Nov 2012. Please direct administrative inquiries to Jonathan Winters at jonathan.winters@nyu.edu and substantive inquiries to Jennifer or me. (2) The Earth Institute Postdoctoral Fellows program ! Every year a select group of recent Ph.D.s in a variety of fields come to the Earth Institute for this two-year research fellowship. I’d love to see more statisticians applying. To apply, candidates must compl
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Introduction: Francis Tuerlinckx announces that he and Denny Borsboom have a joint postdoctoral position. It sounds really cool: The position is in the Research Group of Quantitative Psychology and Individual Differences at the University of Leuven (Belgium) and involves frequent travel to and contact with the Psychological Methods group in Amsterdam. The research of the postdoc will be part of a larger program aimed at developing and applying methods for network analysis in psychology and psychopathology (see a recent review on the topic: Borsboom & Cramer, 2013). The specific research topic will depend on the expertise and interest of the candidate, but will involve one or more of the following: Statistical methods for high dimensional data, multilevel modeling, or nonlinear dynamical models. Interested candidates are encouraged to contact Francis Tuerlinckx (francis.tuerlinckx@ppw.kuleuven.be) and Denny Borsboom (dennyborsboom@gmail.com) for more information. Review of applications will c
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Introduction: Two positions open in the statistics group at the NYU education school. If you get the job, you get to work with Jennifer HIll! One position is a postdoctoral fellowship, and the other is a visiting professorship. The latter position requires “the demonstrated ability to develop a nationally recognized research program,” which seems like a lot to ask for a visiting professor. Do they expect the visiting prof to develop a nationally recognized research program and then leave it there at NYU after the visit is over? In any case, Jennifer and her colleagues are doing excellent work, both applied and methodological, and this seems like a great opportunity.
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1 0.96265185 933 andrew gelman stats-2011-09-30-More bad news: The (mis)reporting of statistical results in psychology journals
Introduction: Another entry in the growing literature on systematic flaws in the scientific research literature. This time the bad tidings come from Marjan Bakker and Jelte Wicherts, who write : Around 18% of statistical results in the psychological literature are incorrectly reported. Inconsistencies were more common in low-impact journals than in high-impact journals. Moreover, around 15% of the articles contained at least one statistical conclusion that proved, upon recalculation, to be incorrect; that is, recalculation rendered the previously significant result insignificant, or vice versa. These errors were often in line with researchers’ expectations. Their research also had a qualitative component: To obtain a better understanding of the origins of the errors made in the reporting of statistics, we contacted the authors of the articles with errors in the second study and asked them to send us the raw data. Regrettably, only 24% of the authors shared their data, despite our request
Introduction: The story starts in September, when psychology professor Fred Oswald wrote me: I [Oswald] wanted to point out this paper in Science (Ramirez & Beilock, 2010) examining how students’ emotional writing improves their test performance in high-pressure situations. Although replication is viewed as the hallmark of research, this paper replicates implausibly large d-values and correlations across studies, leading me to be more suspicious of the findings (not less, as is generally the case). He also pointed me to this paper: Experimental disclosure and its moderators: A meta-analysis. Frattaroli, Joanne Psychological Bulletin, Vol 132(6), Nov 2006, 823-865. Disclosing information, thoughts, and feelings about personal and meaningful topics (experimental disclosure) is purported to have various health and psychological consequences (e.g., J. W. Pennebaker, 1993). Although the results of 2 small meta-analyses (P. G. Frisina, J. C. Borod, & S. J. Lepore, 2004; J. M. Smyth
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Introduction: The deadline for this year’s Earth Institute postdocs is 1 Dec, so it’s time to apply right away ! It’s a highly competitive interdisciplinary program, and we’ve had some statisticians in the past. We’re particularly interested in statisticians who have research interests in development and public health. It’s fine–not just fine, but ideal–if you are interested in statistical methods also.
4 0.94527692 984 andrew gelman stats-2011-11-01-David MacKay sez . . . 12??
Introduction: I’ve recently been reading David MacKay’s 2003 book , Information Theory, Inference, and Learning Algorithms. It’s great background for my Bayesian computation class because he has lots of pictures and detailed discussions of the algorithms. (Regular readers of this blog will not be surprised to hear that I hate all the Occam -factor stuff that MacKay talks about, but overall it’s a great book.) Anyway, I happened to notice the following bit, under the heading, “How many samples are needed?”: In many problems, we really only need about twelve independent samples from P(x). Imagine that x is an unknown vector such as the amount of corrosion present in each of 10 000 underground pipelines around Cambridge, and φ(x) is the total cost of repairing those pipelines. The distribution P(x) describes the probability of a state x given the tests that have been carried out on some pipelines and the assumptions about the physics of corrosion. The quantity Φ is the expected cost of the repa
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Introduction: Guy asks: I am analyzing an original survey of farmers in Uganda. I am hoping to use a battery of welfare proxy variables to create a single welfare index using PCA. I have quick question which I hope you can find time to address: How do you recommend treating count data? (for example # of rooms, # of chickens, # of cows, # of radios)? In my dataset these variables are highly skewed with many responses at zero (which makes taking the natural log problematic). In the case of # of cows or chickens several obs have values in the hundreds. My response: Here’s what we do in our mi package in R. We split a variable into two parts: an indicator for whether it is positive, and the positive part. That is, y = u*v. Then u is binary and can be modeled using logisitc regression, and v can be modeled on the log scale. At the end you can round to the nearest integer if you want to avoid fractional values.
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