Summer School on Robust Statistics
First announcement of the Summer School on Robust Statistics for Personality and Individual Differences on July, 16-21, 2011 in Bertinoro, Italy
Organizers: Jens B. Asendorpf & Marco Perugini
Supported by European Association of Personality Psychology (EAPP)
International Society for the Study of Individual Differences (ISSID)
Traditional parametric statistical procedures such as the Pearson correlation, regression, and tests of group differences by t tests and analysis of variance depend much more on unrealistic assumptions than most psychologists believe. Biased results due to extreme cases such as outliers or mixed distributions of a small extreme group and a much larger normal group are common in psychology, and may be one of the major reasons for the embarrassingly low replicability of findings in psychological research. In recent years, numerous alternatives to parametric statistics have been developed, called robust statistics (see overview by Erceg-Hurn et al., American Psychologist, 2008), and have been implemented in freely available statistical packages such as R. In addition, there is a recent increase in applying bootstrapping for robust estimations of confidence intervals (e.g., replacement of the Sobel test in mediation analyses by bootstrapping procedures; new bootstrapping option for most major statistical tests from SPSS 18.0 on), and in controlling significance levels in correlational matrices through randomization.
The aim of the summer school on robust statistics is to make participants familiar with major robust statistical methods and their implementation in R. Participants will be encouraged to bring own data for analyses under supervision of faculty members.
Teaching faculty includes:
Rand R. Wilcox, U Southern California
Jens B. Asendorpf, Humboldt University Berlin, Germany
Felix Schönbrodt, U Munich, Germany
Ryne A. Sherman, U California at Riverside
Deadline for applications: March 1st, 2011
Application details will be announced in January 2011