Monthly Archives: April 2012

Short R script to plot effect sizes (Cohen’s d) and shade overlapping area

April 23, 2012
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Short R script to plot effect sizes (Cohen’s d) and shade overlapping area

Update: I have created an interactive effect size visualization here Introduction to effect sizes Many times you read in a study that “x and y were significantly different, p < .05”, which is another way of saying that “assuming that the null hypothesis is true, the probability of getting the observed value simply by chance alone is less than 0.05” But that’s not really...

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Drop-Down Menus for R

April 23, 2012
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A few days ago, Andrew Barr had a great post on his blog. It was titled, "R is not just for nerds....it has drop-down menus!" You can bet that this one caught my eye when it was re-posted on R-Bloggers.Briefly, Andrew takes us through the installation and basic use of the Java Gui for R (JGR) in...

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Introduction to Oracle R Connector for Hadoop

April 23, 2012
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MapReduce, the heart of Hadoop, is a programming framework that enables massive scalability across servers using data stored in the Hadoop Distributed File System (HDFS). The Oracle R Connector for Hadoop (ORCH) provides access to a Hadoop cluster from R, enabling manipulation of HDFS-resident data and the execution of MapReduce jobs. Conceptutally, MapReduce is similar...

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Talk on quantiles at the R Montreal group

April 23, 2012
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Talk on quantiles at the R Montreal group

This afternoon, I will be giving a two-hour talk at McGill on quantiles, quantile regressions, confidence regions, bagplots and outliers. Before defining (properly) quantile regressions, we will mention regression on (local) quantiles, as on the gr...

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Puzzle: A path through pairs making squares

April 23, 2012
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Puzzle: A path through pairs making squares

Ted Harding posed an interesting puzzle challenge on the r-help mailing list recently. Here's the puzzle: Take the numbers 1, 2, 3, etc. up to 17. Can you write out all seventeen numbers in a line so that every pair of numbers that are next to each other, adds up to give a square number? You can figure out...

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Tuning GAMBoost

April 23, 2012
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Tuning GAMBoost

This post describes some of the simulation results which I obtained with the GAMBoost package. The aim of these simulations is to get a feel what I should tune and what I should not tune with GAMBoost. SetupIn the GAMBoost package one can tune qui...

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Example 9.28: creating datasets from tables

April 23, 2012
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Example 9.28: creating datasets from tables

RThere are often times when it is useful to create an individual level dataset from aggregated data (such as a table). While this can be done using the expand.table() function within the epitools package, it is also straightforward to do directly within R.Imagine that instead of the individual level data, we had only the 2x2 table for the...

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Quantitative palaeolimnology: my book chapters are finally out!

April 23, 2012
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Quantitative palaeolimnology: my book chapters are finally out!

Today I received confirmation that the delayed fifth volume in the Developments in Palaeoenvironmental Research series has been published. The book is titled Data Handling and Numerical methods, though it covers more of the latter and, IMHO, is far more interesting than … Continue reading →

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Updates to the Emacs Starter Kit for the Social Sciences

April 23, 2012
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I've made some updates to the Emacs Starter Kit for the Social Sciences. The kit builds on Phil Hagelberg's original and Eric Schulte's org-mode version, and incorporates some packages and settings that are particularly useful for the social sciences. ...

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Probit/Logit Marginal Effects in R

April 23, 2012
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Probit/Logit Marginal Effects in R

The common approach to estimating a binary dependent variable regression model is to use either the logit or probit model. Both are forms of generalized linear models (GLMs), which can be seen as modified linear regressions that allow the dependent variable to originate from non-normal distributions. The coefficients in a linear regression model are marginal

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