## Monday, May 24, 2010

### Great Measurement but Small Sample Size: Case Study of Videotaped Families

New York Times
reports
on an interesting UCLA study
that involved video taping 32 Los Angeles families over the course of a week.
The study generated rich data for analysis.
It's great to see researchers moving beyond self-report measures towards
real-world well-coded behavioural observations.
However, great measurement does not overcome issues of a small sample size.

## Thursday, May 20, 2010

### Inverting a Logistic Function

I was recently talking to a researcher who had conducted a cognitive experiment that involved experimentally manipulating a variable

`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 `x`

at which the
fitted logistic regression function equalled 0.5.
### Fitting Nonlinear Regression Models to Multiple Participants Using SPSS

This post briefly discusses how to run a nonlinear regression in SPSS.
Specifically, it discusses the scenario where you have a a set of

`k`

observations
for each of `n`

participants,
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

### A 34 Minute Video on Using R to Analyse Winter Olympic Medal Data

In this post I present a 34-minute video on using R.
The video is based on
an analysis of 1924 to 2006 Winter Olympic Medals that I presented previously in text form.
The video aims to to show what an interactive session in R might look like using StatET and Eclipse.

## Monday, May 10, 2010

### Abbreviations of R Commands Explained: 250+ R Abbreviations

The R programming language includes many abbreviations.
Abbreviations exist in function names, argument names, and allowed values for arguments.
This post expands on over 150 R abbreviations with the aim of making it easier
for users new to R who are trying to memorise R commands.

## Wednesday, May 5, 2010

### Statistical Power Analysis in G*Power 3

G*Power 3 is an excellent piece of software for performing statistical
power analysis.
It is particularly useful for applied researchers who
need to perform a power analysis as part of their research.
The software is free, runs on Windows, and provides a user friendly GUI.
G*Power 3 can be downloaded here
This post discusses the features of G*Power 3 and provides examples of
some of the useful plots that can be generated.

### Videos on Data Analysis with R: Introductory, Intermediate, and Advanced Resources

If you want to learn about R through videos,
there are now a large number of options.
This post provides links to many of these video under the headings of:
(a) What is R?
(b) Introductory R, and
(c) Intermediate and Advanced R.

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