Future Topics

Topics for the future

Session style:

  • Primarily group discussion, not formal presentations
  • Based around key methodology and application papers which will be put up on this site (try to read before you come along).
  • Discussion is free to extend to broader topics
  • Occasionally we may include other sessions such as "how to…", help clinics, software applications etc.

This website will be used as a repository for associated reading. It will contain the focus method and application papers ahead of the sessions. Please email interesting and relevant papers you know on the topics for discussion to Tom (ku.ca.de|htoob.mot#ku.ca.de|htoob.mot), Aja (ku.ca.de.sms|3285870s#ku.ca.de.sms|3285870s) or Tim (ku.ca.de|setab.mit#ku.ca.de|setab.mit), and we will get them stored on line.

Please also send suggestions for topics. Below (under Topics for future sessions) is the list of possible sessions so far, but let us know if you see something interesting.

Upcoming Sessions


Does Bayesian estimation supersede the t test?

  • Kruschke, J.K. (2012) Bayesian estimation supersedes the t test. Journal of Experimental Psychology: General pdf

"Likert or Rasch? Nothing is more applicable than good theory"

  • van Alphen, A. Halfens, R., Hasman A. and Imbos, T. (1994). Likert or Rasch? Nothing is more applicable than good theory. Journal of Advanced Nursing, 20, 196-201.

Model selection.

  • Vrieze, S.I. (2012). Model selection and Psychological Theory: A discussion of the difference between AIC and BIC. Psychological Methods, 17, 228-243.

Cross-discipline research and analysis.

  • Tucker-Drob, E.M. (2011). Individual differences methods for randomized experiments. Psychological Methods, 16, 298-318.

Non-normal data (skew/kurtosis).

  • Bishara, A. J., & Hittner, J. B. (2012, May 7). Testing the Significance of a Correlation With Nonnormal Data: Comparison of Pearson, Spearman, Transformation, and Resampling Approaches. Psychological Methods. Advance online publication. doi: 10.1037/a0028087

Missing data.

  • Amanda C. Gottschall, Stephen G. West & Craig K. Enders (2012): A Comparison of Item-Level and Scale-Level Multiple Imputation for Questionnaire Batteries, Multivariate Behavioral Research, 47, 1-25

Confounding and suppression in regression.

  • Jason W. Beckstead (2012): Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression, Multivariate Behavioral Research, 47, 224-246.

Response bias: Modelling ipsative data.

  • Brown, A., & Maydeu-Olivares (2011). Item response modeling of forced-choice questionnaires. Educational and Psychological Measurement, 71, 460-502.


  • Pearl, J. (2012). The causal foundations of structural equation modelling. In R. H. Hoyle (Ed). Handbook of Structural Equation Modeling. New York; Guilford Press.

Mediation and moderation.

  • Imai, K. et al. (2010). A general approach to causal mediation analysis. Psychological Methods, 15, 309-334.

Cause and Effect indicators (formative & reflective models).

  • Bollen, K.A., & Bauldry, S. (2011). Three C’s in Measurement Models: Causal Indicators, composite indicators and covariates. Psychological Methods, 16, 265-284.


Graphical Models

Network Analysis

Longitudinal Data Analysis

Cluster Analysis

Bayesian statistics

  • Baysian SEM - a resolution to some practical problems in individual differences?
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