Tuesday, December 28, 2010
Monday, December 13, 2010
As previously mentioned I gave a talk at Melbourne R Users Group titled "Reproducible Research and R Workflow". It covered technologies including LaTeX, Sweave, R, make, Eclipse, and git. This post shares the video.
Thursday, December 2, 2010
Tuesday, November 30, 2010
Monday, November 29, 2010
This post documents an example of using Sweave
to generate individualised personality reports based on
responses to a personality test.
Each report provides information on both the responses of the general
sample and responses of the specific respondent.
All source code is provided, and selected aspects are discussed,
makefiles use of
\Sexpr, figures, and LaTeX tables using Sweave.
(a) installing Git using the Eclipse plugin Egit. (b) uploading repositories to GitHub, and (c) links to resources on Git, Git and LaTeX, and Git and R. The focus is on version control for people working on R, Sweave, and LaTeX related projects.
Saturday, November 27, 2010
Tuesday, November 23, 2010
makefiles. In particular it describes how to set up
makeon Windows with an emphasis on using
makein Eclipse on projects involving R, Sweave, and LaTeX.
Friday, November 12, 2010
This post sets out how to calculate confidence intervals for correlations using R. Because I often get this question from people unfamiliar with R, it assumes no prior knowledge of R.
Saturday, October 23, 2010
Wednesday, August 25, 2010
Thursday, August 5, 2010
Friday, July 30, 2010
Monday, July 19, 2010
Thursday, June 17, 2010
Wednesday, June 2, 2010
Monday, May 24, 2010
Thursday, May 20, 2010
x, a continuous property of a stimulus, looking at the effect on a variable
p, the probability of giving a response. The function p(x) was assumed to be a logistic function. The researcher wanted to know how to calculate the point on
xat which the fitted logistic regression function equalled 0.5.
kobservations for each of
nparticipants, and where your aim is to fit a nonlinear function to the data of each participant in order to save the parameter estimates for subsequent analysis. This is a relatively common task in psychology. You have multiple participants measured on a numeric repeated measures variable and you want to see how a dependent variable is related to this repeated measures variable. And you want to do this separately for each participant. For example, you might be modelling performance as a function of practice or accuracy as a function of stimulus intensity.
Sunday, May 16, 2010
Monday, May 10, 2010
Wednesday, May 5, 2010
Friday, April 23, 2010
Thursday, April 22, 2010
Free Video Courses on R, Structural Equation Modelling, Causal Inference, and Regression from Uni Jena
Wednesday, April 21, 2010
Tuesday, April 20, 2010
Monday, April 19, 2010
Saturday, April 17, 2010
Friday, April 16, 2010
Monday, April 12, 2010
(a) You need to extract a subset of references for a subject you are teaching.
(b) You need to give a colleague or research student a subset of your references.
(c) You want to transfer a subset of your references to another device or computer.
Friday, March 26, 2010
Wednesday, March 24, 2010
RSS Feed: http://feeds.feedburner.com/jeromyanglim
STATISTICS, R, SPSS, RESEARCH DESIGN
- Getting Started: General advice on statistics for a thesis; Statistics lecture notes;
- R: Learning R; Blogs on R; R in Australia; StatET; Tips for StatET; Upgrade procedure; R and Excel; Efficient variable selection in R; Memory Management in R; Optimising Code in R; Analysis of Winter Olympic Medals in R; Regular expressions in R;
- SPSS: Efficient variable selection;
- Preliminaries: Normality and transformations; Independence of observations;
- Scales: Scale construction; Scale construction for psychological tests; Computing Ability Scales; Checking for accuracy; Multiple choice tests; Scoring a multiple choice test in SPSS;
- Mediation: Getting Started; Issues with causal inference;
- Correlations: Two independent correlations; Formatting a correlation matrix; Adjusting for reliability; Tetrachoric correlations; Confidence intervals; Significance tests; Difference Scores;
- Repeated Measures: Longitudinal data; Data structuring for repeated measures experiments;
- Dyadic Data: Data management; Basic analyses;
- Basic Analyses: Basic procedure for observational study; Introduction to Modelling;
- ANOVA: Follow up tests;
- Regression: Variable importance in multiple regression; Multinomial logistic regression; Generalised estimating equations; Model building; Logistic Regression;
- Factor Analysis: Item parcelling; Factor analysis and scale construction; Factor analysis in R;
- Data Mining: Data mining and R
- SEM: SEM in R; SEM resources;
- Assorted: Bootstrapping in R; Discriminant function analysis; Problems with cluster analysis; Ordinal variables; Meta Analysis;
- Results: Tables R to Word; Grammar of tables; Data sharing and literate programming; Table of item descriptives;
- Maths: Free mathematics video courses; Free online mathematics books; Symbol pronunciation; Matrix Algebra in R; Reading mathematics;
- Research Design: Carryover effects; Causal Inference; Depth interviews; Designing online experiments;
Friday, March 19, 2010
Monday, March 15, 2010
This post discusses my experience getting APA style references in LaTeX. This includes both in-text citations and the end of document references list. It focuses on the use of the