Monday, December 21, 2009
Thursday, December 17, 2009
Tuesday, December 15, 2009
Friday, December 11, 2009
Wednesday, December 9, 2009
Tuesday, December 8, 2009
Monday, December 7, 2009
Wednesday, December 2, 2009
Monday, November 23, 2009
Monday, November 16, 2009
Sunday, November 15, 2009
Monday, November 9, 2009
Thursday, November 5, 2009
Monday, November 2, 2009
Friday, October 30, 2009
Thursday, October 29, 2009
Monday, October 26, 2009
Saturday, October 24, 2009
Friday, October 23, 2009
Wednesday, October 21, 2009
Tuesday, October 20, 2009
The ideas link in with the concerns of myself and others with reproducible research, data sharing, data analysis, and open publishing.
IBM has now released version 18 of PASW. I was trying to find out what were the new features in version 18, when I stumbled on a potential problem with the new name, and perhaps some reasons why IBM may want to move out of troubling teen version numbers as quickly as possible.
"[MyKi project’s new spokeswoman] said that Government focus groups had shown that Melburnians were looking forward to using the new card." - TheAgeI just wanted to make a few comments about problems in the reasoning of the above quote.
Monday, October 19, 2009
I have presented research on social network analysis to several forums including to organisational and educational psychology audiences. In these settings the audience varies substantially in their prior exposure to social networks analysis. Researchers new to social network analysis often then ask me where they should start in order to learn about the theories and methods of social network analysis. This post aims to provide some links to get such an interested researcher started.
Theresa has also developed a set of course notes on R, R Commander, Latex and Sweave, and Excel.
Friday, October 9, 2009
Thursday, October 8, 2009
Wednesday, October 7, 2009
Monday, October 5, 2009
Sunday, October 4, 2009
Saturday, October 3, 2009
Friday, October 2, 2009
"Nigel, who has an IQ of 180, is also a maths whiz.." - The AgeThis got me thinking. What does it mean to have a 180 IQ. IQ is a norm score. IQ typically has a mean of 100 and a standard deviation of 15. Thus, I asked the following questions:
- What's the probability of having an IQ of 180 or higher?
- One in how many people would have an IQ 180 or higher?
- What's is the probability that someone who a newspaper reports as having a 180 IQ or higher, actually has an IQ of 180 or higher?
Tuesday, September 29, 2009
A difference score is a variable that has been formed by subtracting one variable from another.
DIFFSCORE = VAR1 - VAR2.
Some researchers have heard that difference scores are 'bad'. This post discusses some of the issues, provides some additional references, and discusses calculating reliability of difference scores.
Monday, September 28, 2009
It is an interesting case study in how to integrate R into a psychology quantitative methods course at the undergraduate level. It's also a cool example of integrating web resources.
Saturday, September 26, 2009
Friday, September 25, 2009
"A SPANK on the bottom, long used by parents to discipline a naughty child, could cause more than tears... It's now thought the age-old disciplinary method may also lower a child's IQ, with those spanked up to three times a week having a lower IQ due to psychological stress."
Thursday, September 24, 2009
Wednesday, September 23, 2009
- Formatting correlation matrices into psychological format using SPSS, Excel and Word
- One-group observational study: Basic set of analyses with links to SPSS resources
- Longitudinal data: Basic data management and analyses
- dyadic data: Basic data analysis and how to merge data in SPSS in dyadic data situations.
- Carry-over effects in repeated measures designs: what to think about and a case study from my own research
- Issues of causal inference in mediation analysis and basic resources for performing mediation and moderation analyses.
Tuesday, September 22, 2009
Monday, September 21, 2009
Something to aspire to:
- Raw data is shared (ethics, copyright, and other considerations permitting).
- Code is shared that shows how the data was imported, transformed, and analysed. This code is well written, commented, and documented.
- The report is shared as opposed to requiring a paid subscription.
- Report output including tables, figures, and some text is linked directly to the analyses in code.
While the aspirations transcend R, I like the prospect of having analyses in R integrated with a final report. The inclusion of tables and figures , at least conceptually is a straightforward idea. However, the inclusion of text in a results section is a little fuzzier. Surely, text in a results section (I'll call it "results text" for short) varies in how it relates to actual analyses. Thus, I had the following questions: 1) What is the unit of results text? 2) How does results text vary and what should be automatically supplied by R?; 3) For results text that should not be supplied by R, how should it be integrated into an analysis process?
Initial thoughts: After a little reflection I had the following thoughts:
Saturday, September 19, 2009
Friday, September 18, 2009
Thursday, September 17, 2009
Tuesday, September 15, 2009
The details below set out my setup for my blog account and my blogging statistics. When I set it up originally, I did look into the various options in terms of blogging providers and so on. I make no claim to my choices being optimal for me or other people. But I have found them more than adequate for my purposes. In particular, usage statistics (and comments) are a great form of feedback that is not necessarily available in other forms of academic communication. For further discussion of the benefits of blogging and related technologies in academic, Gideon Burton provides a great exposition.
A researcher recently asked me how to calculate confidence intervals for two correlations that share a common variable (i.e., dependent correlations).
Thursday, September 10, 2009
Wednesday, September 9, 2009
- 5 x 3 Design: 5 levels of task type (repeated measures); and 3 levels of group (between subjects)
- 2 x 2 x 2 Design: 2 levels of order (between subjects); by 2 levels of instructions (between subjects); by 2 levels of task feature (repeated measures)
Tuesday, September 8, 2009
Monday, September 7, 2009
Wednesday, September 2, 2009
Create a long format data file called “trials” where each row is the combination of one participant and one trial. And have a separate data file called “subjects” that contains one row per participant and includes data on participants that is constant throughout the experiment (e.g., gender, age, personality measures, etc.).
Tuesday, August 18, 2009
Social Network Analysis is an increasingly popular tool for modelling dependence structures between social actors. In my department researchers are developing new models for representing such dependence structures (MELNET). In 2007 I gave a talk on my consulting experience using social network analysis to provide insights on team dynamics. Since then I have switched to mainly using R for analysing social network datasets.
Monday, August 17, 2009
I see the issue as involving two elements:
- What criterion of an effective selection system does the university want to use?
- What measurement system can be put in place to maximise this criterion?
The first issue is a matter of values and policy. The second issue is empirical.
From The Age article I gather that there is concern for: representation from disadvantaged student groups and academic potential.
Wednesday, August 5, 2009
Friday, June 12, 2009
Saturday, June 6, 2009
R is a powerful open source environment for statistical computing. This post provides a selective list of resources for getting started with R including thoughts on books, online manuals, blogs, videos, user interfaces, and more. At the end of the post are some R resources specific to researchers in psychology. (UPDATED 4th May 2011)
Friday, May 29, 2009
Mathematics Pronunciation Guides
- VÄliaho's guide to Pronunciation of Mathematical Expressions: This is the place to start. It covers many important rules in a 3 page document
- Handbook for Spoken Mathematics: If VÄliaho's guide did not meet your requirements, check out this extensive resource. It covers many major branches of mathematics such as logic and set theory, geometry, statistics, calculus, and linear algebra. It is the most comprehensive guide that I have found with around 100 pages and around 500 symbols with pronunciation. I'd recommend studying all the symbols if mathematical pronunciation is an issue for you. The symbols are distributed over many pages making it a little difficult to look up a single symbol of interest. Also, when a choice exists, the guide often chooses a more verbose and less ambiguous form of pronunciation. For example, it suggests for "x_i", "x sub i" instead of "x i". This emphasis on unambiguous verbal communication is sometimes more than required when verbalising the symbols in your head or when verbalising symbols in a context where the actual symbolic math is also displayed.
- RPI's Saying Mathematics Guide
- Oanca et al's Reading Mathematical Expressions
- Wikipedia guide to mathematical symbols: meaning of common mathematical symbols with links to their meaning.
- Greek letters: Lower and upper case Greek letters with pronunciation
- Tips on displaying formulas can even be useful for some obscure mathematical symbols
Books on mathematical pronunciation
- Lawrence Change (1983). Handbook for Spoken Mathematics: (Larry's Speakeasy).
Thursday, May 28, 2009
Today I gave an introductory talk for the Neuropsychological Students’ Society at the University of Melbourne on the topic of Statistical Modelling in Psychology.
The slides with notes from the talk are available for download at the following link: Introduction to Statistical Modelling in Psychology.
Friday, May 22, 2009
I was recently asked about options for bootstrapping. The following post sets out some applications of bootstrapping and strategies for implementing it in R. I've found bootstrapping useful in several settings:
- where the statistic I'm interested in is a little unusual: the average R-square across five separate regressions; the difference in the average correlation of a set of variables between two groups
- non parametric statistics, such as the median
- when assumptions such as normality of homoscedasticity are not satisfied
Thursday, May 21, 2009
Wednesday, May 20, 2009
Friday, May 15, 2009
In 2007 I presented a talk to postgraduate psychology students at The University of Melbourne. As part of the talk I produced a handout which summarised many of the key points that I felt were relevant for such an audience who needed to complete a thesis involving quantitative analysis. Reading over it two years later, I still agree with the ideas, even if my understanding may be a little more nuanced. For example, I'd now see meta-analytic thinking as a simple version of Bayesian statistics. Anyway, I thought I'd post it on the blog.