This exciting one-day workshop is aimed at doctoral students in both psychology and economics. In the morning session "Analysing Psychological Data Using Mixed-Effects Models", we will describe new ways in which psychologists are attempting to find patterns in data collected from experiments or from naturalistic samples.
We will explain why the R statistical programming language is gaining traction in Psychology, and we will offer examples of the kinds of research designs and analyses that mixed-effects models make possible; and we will offer guidance on current best practice for analyses. We will present evidence from recent simulations suggesting that mixed-effects models should be used with caution, and show that, in some situations, good-old ANOVA is still a useful statistical tool.
The afternoon session, "Incorporating Subjective and Psycholmetric Measures into Economics: Issues and Applications", examines the use of self-reported or subjective measures in economic applications. Firstly we examine survey design and principles for sound construction of survey measures. Secondly we examine basic linear and non-linear econometric methods for the analysis of survey data. Thirdly we examine the use of subjective measures as dependent variables in standard regression designs. In particular, we consider differential item functioning, namely respondents to survey questions using different criteria for judging what the question means. Finally, we examine the incorporation of self-reported and subjective measures in economic studies as explanatory variables explaining outcomes such as health and education.