Middle-aged white death trends update: It’s all about women in the south

January 19, 2016
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Middle-aged white death trends update:  It’s all about women in the south

Jonathan Auerbach and I wrote up some of the age-adjustment stuff we discussed on this blog a couple months ago. Here’s our article, a shorter version of which will appear as a letter in PPNAS. And here’s the new analysis we did showing age-adjusted death rates for 45-54-year-old non-Hispanic white men and women: Wow!! Remember […] The post Middle-aged white death trends update: It’s all about women in the south…

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Formatting table output in R

January 19, 2016
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Formatting table output in R

Formatting data for output in a table can be a bit of a pain in R. The package formattable by Kun Ren and Kenton Russell provides some intuitive functions to create good looking tables for the R console or HTML quickly. The package home page demonstrat...

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My namesake doesn’t seem to understand the principles of decision analysis

January 18, 2016
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My namesake doesn’t seem to understand the principles of decision analysis

It says “Never miss another deadline.” But if you really could never miss your deadlines, you’d just set your deadlines earlier, no? It’s statics vs. dynamics all over again. That said, this advice seems reasonable: The author has also developed a foolproof method of structuring your writing, so that you make effective use of your […] The post My namesake doesn’t seem to understand the principles of decision analysis appeared…

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On deck this week

January 18, 2016
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Mon: My namesake doesn’t seem to understand the principles of decision analysis Tues: Middle-aged white death trends update: It’s all about women in the south Wed: My talk Fri 1pm at the University of Chicago Thurs: If you’re using Stata and you want to do Bayes, you should be using StataStan Fri: One quick tip […] The post On deck this week appeared first on Statistical Modeling, Causal Inference, and…

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MCqMC 2016

January 18, 2016
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MCqMC 2016

After the MCqMC 2014 conference in Leuven I enjoyed very much, the MCqMC 2016 instalment takes place in Stanford this (late) summer. I cannot alas attend it, as I will be in Australia all summer winter, but the program looks terrific! As Art’s tutorial so brilliantly showed at MCMskv last week, the connections between the […]

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Confidence Regions for Parameters in the Simplex

January 18, 2016
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Confidence Regions for Parameters in the Simplex

Consider here the case where, in some parametric inference problem, parameter  is a point in the Simplex, For instance, consider some regression, on compositional data, > library(compositions) > data(DiagnosticProb) > Y=DiagnosticProb[,"type"]-1 > X=DiagnosticProb[,c("A","B","C")] > model = glm(Y~ilr(X),family=binomial) > b = ilrInv(coef(model)[-1],orig=X) > as.numeric(b) [1] 0.3447106 0.2374977 0.4177917 We can visualize that estimator on the simplex, using > tripoint=function(s){ + p=s/sum(s) + abc2xy(matrix(p,1,3)) + } > lab=LETTERS[1:3] > xl=c(-.1,1.25) > yl=c(-.1,1.15) >…

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Create a SAS macro variable that contains a list of values

January 18, 2016
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Create a SAS macro variable that contains a list of values

Parameters in SAS procedures are specified a list of values that you manually type into the procedure syntax. For example, if you want to specify a list of percentile values in PROC UNIVARIATE, you need to type the values into the PCTLPTS= option as follows: proc univariate data=sashelp.cars noprint; var […] The post Create a SAS macro variable that contains a list of values appeared first on The DO Loop.

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Measuring Policy Uncertainty and its Effects

January 18, 2016
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Fascinating work like Baker, Bloom and Davis (2015) has for some time had me interested in defining and measuring policy uncertainty and its effects. A plausible hypothesis is that policy uncertainty, like inflation uncertainty, reduces aggre...

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Grizzly Adams is an object of the class Weekend at Bernies

January 18, 2016
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Grizzly Adams is an object of the class Weekend at Bernies

It just came to me when I saw his obit. The post Grizzly Adams is an object of the class Weekend at Bernies appeared first on Statistical Modeling, Causal Inference, and Social Science.

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The normal distribution – three tricky bits

January 18, 2016
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The normal distribution – three tricky bits

There are several tricky things about teaching and understanding the normal distribution, and in this post I’m going to talk about three of them. They are the idea of a model, the limitations of the normal distribution, and the idea … Continue reading →

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Set up RStudio in the cloud to work with GitHub

January 17, 2016
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Set up RStudio in the cloud to work with GitHub

I love GitHub for version control and collaboration, though I'm no master of it. And the tools for integrating git and GitHub with RStudio are just amazing boons to productivity. Unfortunately, my University-supplied computer does not play well with ...

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Nina Zumel and John Mount part of R Day at Strata + Hadoop World in San Jose 2016

January 17, 2016
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Nina Zumel and I are honored to have been invited to be part of Strata + Hadoop World in San Jose 2016 R Day organized by RStudio and O’Reilly. We have written a lot on the topic of model validation in R and we are very excited to distill it down to an exciting tutorial. … Continue reading Nina Zumel and John Mount part of R Day at Strata +…

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A simple ANOVA

January 17, 2016
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A simple ANOVA

I was browsing Davies Design and Analysis of Industrial Experiments (second edition, 1967). Published by for ICI in times when industry did that kind of thing. It is quite an applied book. On page 107 there is an example where the variance of a pr...

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The devil really is in the details; or, You’ll be able to guess who I think are the good guys and who I think are the bad guys in this story, but I think it’s still worth telling because it provides some insight into how (some) scientists view statistics

January 17, 2016
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I noticed this on Retraction Watch: “Scientists clearly cannot rely on the traditional avenues for correcting problems in the literature.” PubPeer responds to an editorial slamming the site. I’ve never actually read anything on PubPeer but I understand it’s a post-publication review site, and I like post-publication review. So I’m heading into this one on […] The post The devil really is in the details; or, You’ll be able to…

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Why Does "Pi" Appear in the Normal Density

January 16, 2016
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Why Does "Pi" Appear in the Normal Density

Every now and then a student will ask me why the formula for the density of a Normal random variable includes the constant, π, or more correctly (2π)-½.The answer is that this term ensures that the density function is "proper" - that is, the integra...

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Scientists Not Behaving Badly

January 16, 2016
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Scientists Not Behaving Badly

Andrea Panizza writes: I just read about psychologist Uri Simonson debunking a research by colleagues Raphael Silberzahn & Eric Uhlmann on the positive effects of noble-sounding German surnames on people’s careers (!!!). Here the fact is mentioned. I think that the interesting part (apart, of course, from the general weirdness of Silberzahn & Uhlmann’s research […] The post Scientists Not Behaving Badly appeared first on Statistical Modeling, Causal Inference, and…

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Turkopticon: Defender of Amazon’s Anonymous Workforce

January 16, 2016
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Turkopticon: Defender of Amazon’s Anonymous Workforce

Labor crowdsourcing is the system by which large crowds or workers contribute to a project allowing for complex and tedious tasks to be rapidly and efficiently completed. The largest labor crowdsourcing platform in the world, Amazon Mechancial TURK (Mt...

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Crowdsourcing research

January 16, 2016
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Crowdsourcing research

Last evening, Anthony Goldbloom, the founder of Kaggle.com, gave a very nice talk at a joint Statistical Programming DC/Data Science DC event about the Kaggle experience and what can be learned from the results of their competitions. One of the take away messages was that crowdsourcing data problems to a diligent and motivated group of entrepreneurial data […]

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McElreath’s Statistical Rethinking: A Bayesian Course with Examples in R and Stan

January 15, 2016
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McElreath’s Statistical Rethinking: A Bayesian Course with Examples in R and Stan

We’re not even halfway through with January, but the new year’s already rung in a new book with lots of Stan content: Richard McElreath (2016) Statistical Rethinking: A Bayesian Course with Examples in R and Stan. Chapman & Hall/CRC Press. This one got a thumbs up from the Stan team members who’ve read it, and […] The post McElreath’s Statistical Rethinking: A Bayesian Course with Examples in R and Stan…

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Using Excel versus using R

January 15, 2016
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Here is a video I made showing how R should not be considered “scarier” than Excel to analysts. One of the takeaway points: it is easier to email R procedures than Excel procedures. Win-Vector’s John Mount shows a simple analysis both in Excel and in R. A save of the “email” linking to all code … Continue reading Using Excel versus using R

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Artificial Intelligence: Solving the Chinese Room Argument

January 15, 2016
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Artificial Intelligence: Solving the Chinese Room Argument

Yesterday, the very best AI (artificial intelligence) had trouble beating a novice human chess player. Today, the very best human player has enormous difficulty beating the best AI. Tomorrow, the very best human player will never beat any AI. However, ...

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Unz Ivy Stats Flashback

January 15, 2016
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Unz Ivy Stats Flashback

This news story reminded me of some threads from a few years ago about Ron Unz, the political activist who wrote a statistics-filled article a few years ago claiming that Harvard and other Ivy League colleges discriminate against Asian-Americans and in favor of Jews in undergraduate admissions. It turned out that some of his numbers […] The post Unz Ivy Stats Flashback appeared first on Statistical Modeling, Causal Inference, and…

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When Excel goes bad

January 15, 2016
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As we know Excel is very powerful and very flexible, which is why it gets used for all sorts of data, but the myriad of functions and tools available means we can do all sorts of clever things with our worksheets, from drop down lists to dynamic charts...

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