Update

September 22, 2009
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Update

I can't believe it's been two months since I last posted... wow, time has a way of slipping through my fingers.  Here's a short list of some upcoming posts: An introduction to LSPM -- a new R package that implements Ralph Vince's leverage space po...

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SAS: “The query requires remerging summary statistics back with the original data”

September 22, 2009
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SAS: “The query requires remerging summary statistics back with the original data”

Coming from a background writing SQL code directly for “real” RDBMS (Microsoft SQL Server, MySQL, and SQLite), I was initially confused when SAS would give me the following ‘note’ for a simple summary PROC SQL query: 429 proc sql; 430 create table undel_monthly as 431 select 432 year(date) as year, 433 month(date) as month, 434

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R Function of the Day: table

September 21, 2009
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R Function of the Day: table

The R Function of the Day series will focus on describing in plain language how certain R functions work, focusing on simple examples that you can apply to gain insight into your own data. Today, I will discuss the table function. What situation is table useful in? The table function is a very basic, but

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R Function of the Day: table

September 21, 2009
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Edit: This post originally appeared on my Wordpress blog on September 21, 2009. I present it here in its original form. The R Function of the Day series will focus on describing in plain language how certain R functions work, focusing on si...

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Comparison of plots using Stata, R base, R lattice, and R ggplot2, Part I: Histograms

September 21, 2009
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One of the nicer things about many statistics packages is the extremely granular control you get over your graphical output.  But I lack the patience to set dozens of command line flags in R, and I'd rather not power the computer by pumping the mouse trying to set all the clicky-box options in Stata's graphics editor.  I want something...

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Linking text, results, and analyses: Increasing transparency and efficiency

September 20, 2009
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Linking text, results, and analyses: Increasing transparency and efficiency

I have recently been thinking about the relationship between text in a final report and data analysis. The broader concern is with making the conduct and reporting of statistical analyses more transparent. I am inspired by the ideas of literate program...

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R Function of the Day: tapply

September 20, 2009
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Edit: This post originally appeared on my Wordpress blog on September 20, 2009. I present it here in its original form. The R Function of the Day series will focus on describing in plain language how certain R functions work, focusing on sim...

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Welcome to Sigmafield

September 20, 2009
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Edit: This post originally appeared on my Wordpress blog on September 20, 2009. I present it here in its original form. John Tukey's preface to Exploratory Data Analysis begins with a useful rule, "It is important to understand what you can...

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Structural Equation Modelling in R

September 20, 2009
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Structural Equation Modelling in R

Structural Equation Modelling (SEM) Software is frequently used in psychology. This post discusses the exciting prospect of greater support for SEM in R. ...I have used SEM to:Run confirmatory factor analyses to examine the measurement structure of mul...

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R Function of the Day: tapply

September 20, 2009
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R Function of the Day: tapply

The R Function of the Day series will focus on describing in plain language how certain R functions work, focusing on simple examples that you can apply to gain insight into your own data. Today, I will discuss the tapply function. What situation is tapply useful in? In statistics, one of the most basic activities

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RInside release 0.1.0 — and now on CRAN

September 20, 2009
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Version 0.1.0 of RInside, my C++ wrapper classes which facilitate embedding R into your own C++ application, has been released and is now an official CRAN package. This release improves on the build process and should work on any sane Unix-alike o...

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RInside release 0.1.0 — and now on CRAN

September 20, 2009
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Version 0.1.0 of RInside, my C++ wrapper classes which facilitate embedding R into your own C++ application, has been released and is now an official CRAN package. This release improves on the build process and should work on any sane Unix-alike opera...

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RInside release 0.1.0 — and now on CRAN

September 20, 2009
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Version 0.1.0 of RInside, my C++ wrapper classes which facilitate embedding R into your own C++ application, has been released and is now an official CRAN package. This release improves on the build process and should work on any sane Unix-alike o...

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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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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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Workflow in R

This came up recently on StackOverflow. One of the answers was particularly helpful and I thought it might be worth mentioning here. The idea presented there is  to break the code into four files, all stored in your project directory. These four files are to be processed in the following order. load.R This file includes

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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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Solar Trends: Sunspot Numbers Since 1749

September 17, 2009
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Solar Trends: Sunspot Numbers Since 1749

This is the 1st in a series of  posts I will be doing on solar trends. In this post, I show how to retrieve online monthly sunspot data back to 1749, calculate average annual sunspot numbers (SSN),  plot the monthly and annual average SSN as well as a lowess smooth, add the Solar

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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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Find the function you’re looking for in R

September 14, 2009
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Any R user no matter what level of experience has had trouble finding the package or the function to do what you want to do and then figuring out how to use it.  The sos package in R just made that a lot easier. First, fire up R, then install the sos package (don't omit the quotes): install.packages("sos") It'll ask you to...

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Chicago Half Marathon 2009

September 13, 2009
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Today it was once again time for the Chicago Half Marathon (which I have now been running in 2003, 2004, 2005, 2006, 2007 and 2008). Conditions were much much better than last year's very heavy rainfall---we were once again treated to a sunny and clear Chicago sky. It was however a little on the humid side and got...

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Finding an R function

September 13, 2009
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Finding an R function

Suppose you want a function to fit a neural network. What’s the best way to find it? Here are three steps that help to find the elusive function relatively quickly. First, use help.search("neural") or the shorthand ??neural. This will search the help files of installed packages for the word “neural”. Actually, fuzzy matching is used

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