Monthly Archives: September 2009

Welcome to Blogistic Reflections! (A blog created entirely in Emacs org-mode)

September 19, 2009
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Welcome to Blogistic Reflections! (A blog created entirely in Emacs org-mode)

John Tukey’s preface to Exploratory Data Analysis begins with a useful rule, “It is important to understand what you can do before you learn to measure how well you seem to have done it.” When I decided I wanted to start a blog concentrating on statistics, R, and Emacs, I thought I had better learn

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Power Analysis for mixed-effect models in R

September 18, 2009
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Power Analysis for mixed-effect models in R

The power of a statistical test is the probability that a null hypothesis will be rejected when the alternative hypothesis is true. In lay terms, power is your ability to refine or "prove" your expectations from the data you collect. The most frequent...

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Web-Based Multilevel Modeling

September 18, 2009
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This is tremendously cool. A nice intuitive web-based interface for the lme4 package in R (and you neither need to know R or understand the intricacies of the lme4 package) that gives you pdf output and plots. If you just want to play around and not worry about coding things up, it’s a great little

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Set your R working directory in TextWrangler

Set your R working directory in TextWrangler

Yesterday I figured out (together with a friend, Leendert) how to set your R working directory to the path of the current document you're working on in TextWrangler. We developed two scripts: one for setting the working directory of R directly, and one...

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R Community in Australia

September 17, 2009
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R Community in Australia

One of the nice aspects of R is the community of users that has built up around it. The open-source model seems to create an orientation of sharing and contribution. Users benefit from R and then they give back in the form of new packages, free documen...

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Workflow in R

September 17, 2009
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This came up recently on StackOverflow. One of the answers was particularly helpful and I plan to adopt this for my future work. In fact, it is close to what I already do, but is a little more structured. The idea is to break the code into four files, ...

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Example 7.12: Calculate and plot a running average

September 17, 2009
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Example 7.12: Calculate and plot a running average

The Law of Large Numbers concerns the stability of the mean, as sample sizes increase. This is an important topic in mathematical statistics. The convergence (or lack thereof, for certain distributions) can easily be visualized in SAS and R (see also Horton, Qian and Brown, 2004).Assume that X1, X2, ..., Xn are independent and identically distributed realizations...

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Comments on “Introduction to Scientific Programming and Simulation Using R”

September 17, 2009
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Comments on “Introduction to Scientific Programming and Simulation Using R”

I've just been reading Introduction to Scientific Programming and Simulation Using R by Owen Jones, Robert Maillardet, and Andrew Robinson. It seems like it would make a good introductory book for a course on, as the title suggests, scientific programm...

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R clinic this week: Regression Modeling Strategies in R

September 16, 2009
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At this week's R clinic Frank Harrell will unveil the new rms (Regression Modeling Strategies) package that is a replacement for the R Design package.  He will demonstrate the differences with Design, especially related to enhanced graphics for displaying effects in regression models.  Frank will also discuss the implementation of quantile regression in rms.  The rms package website has...

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Multiple Linear Regression

September 14, 2009
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Multiple Linear Regression

A multiple linear regression (MLR) model that describes a dependent variable y by independent variables x1, x2, ..., xp (p > 1) is expressed by the equation as follows, where the numbers α and βk (k = 1, 2, ..., p) are the parameter...

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