Blog Archives

Using multilevel models to get accurate inferences for repeated measures ANOVA designs

April 18, 2013
By
Using multilevel models to get accurate inferences for repeated measures ANOVA designs

It is now increasingly common for experimental psychologists (among others) to use multilevel models (also known as linear mixed models) to analyze data that used to be shoe-horned into a repeated measures ANOVA design. Chapter 18 of Serious Stats introduces multilevel models by considering them as an extension of repeated measures ANOVA models that can

Read more »

Near-instant high quality graphs in R

September 5, 2012
By
Near-instant high quality graphs in R

One of the main attractions of R (for me) is the ability to produce high quality graphics that look just the way you want them to. The basic plot functions are generally excellent for exploratory work and for getting to know your data. Most packages have additional functions for appropriate exploratory work or for summarizing

Read more »

Confidence intervals with tiers: functions for between-subjects (independent measures) ANOVA

June 21, 2012
By
Confidence intervals with tiers: functions for between-subjects (independent measures) ANOVA

In a previous post I showed how to plot difference-adjusted CIs for between-subjects (independent measures) ANOVA designs (see here). The rationale behind this kind of graphical display is introduced in Chapter 3 of Serious stats (and summarized in my earlier blog post). In a between-subjects – or in indeed in a within-subjects (repeated measures) – design

Read more »

Pasting Excel data into R on a Mac

June 2, 2012
By
Pasting Excel data into R on a Mac

When starting out with R, getting data in and out can be a bit of a pain. It should take long to work out a convenient method – depending on what OS you use and what other packages you work with. In my case I prefer to work with Excel spreadsheets (which are versatile and

Read more »

Updating to R 2.15, warnings in R and an updated function list for Serious Stats

May 27, 2012
By
Updating to R 2.15, warnings in R and an updated function list for Serious Stats

Whilst writing the book  the latest version of R changed several times. Although I started on an earlier version, the bulk of the book was written with 2.11 and it was finished under R 2.12. The final version of the R scripts were therefore run and checked using R 2.12 and, in the main, the most recent

Read more »

R functions for serious stats

March 25, 2012
By
R functions for serious stats

UPDATE: Some problems arose with my previous host so I have now updated the links here and elsewhere on the blog. The companion web site for Serious Stats has a zip file with R scripts for each chapter. This contains examples of R code and and all my functions from the book (and a few extras).

Read more »

Serious stats companion web site now live: sample chapter, data and R scripts

March 23, 2012
By
Serious stats companion web site now live: sample chapter, data and R scripts

The companion web site for Serious stats is now live: http://www.palgrave.com/psychology/Baguley/ It includes a sample chapter (Chapter 15: Contrasts), data sets, R scripts for all the examples and supplementary material. Filed under: news, R code, ser...

Read more »

Independent measures (between-subjects) ANOVA and displaying confidence intervals for differences in means

March 18, 2012
By
Independent measures (between-subjects) ANOVA and displaying confidence intervals for differences in means

In Chapter 2 (Confidence Intervals) of Serious stats I consider the problem of displaying confidence intervals (CIs) of a set of means (which I illustrate with the simple case of two independent means). Later, in Chapter 16 (Repeated Measures ANOVA), I consider the trickier problem of displaying of two or more means from paired or

Read more »

Beware the Friedman test!

February 14, 2012
By
Beware the Friedman test!

In section 10.4.4 of Serious stats (Baguley, 2012) I discuss the rank transformation and suggest that it often makes sense to rank transform data prior to application of conventional ‘parametric’ least squares procedures such as t tests or one-way ANOVA. There are several advantages to this approach over the usual approach (which involves learning and applying a new test such as Mann-Whitney U,

Read more »

Comparing correlations: independent and dependent (overlapping or non-overlapping)

February 5, 2012
By
Comparing correlations: independent and dependent (overlapping or non-overlapping)

In Chapter 6 (correlation and covariance) I consider how to construct a confidence interval (CI) for the difference between two independent correlations.  The standard approach uses the Fisher z transformation to deal with boundary effects (the squashing of the distribution and increasing asymmetry as r approaches -1 or 1). As zr is approximately normally distributed

Read more »