Advanced Linear Mixed Models

In recent years, so-called linear mixed models have become popular in the analysis of data from experimental psychology (e.g., reaction times). An important advantage of these models over classical analyses of variance is that a participant's data from the experimental trials does not have to be aggregated. This enables researchers, for instance, to examine more complex temporal dynamics within an experimental session. In addition, the models can be used to generate estimates of individual subjects' experimental effects so that research questions can be investigated regarding interindividual differences (e.g., Do all subjects respond very similarly to the experimental manipulation? Are there characteristics of the subjects that can explain differences in experimental effects?). This is of particular interest for research which aims to bridge the research-applicatio gap, for example, when objective measures of cognitive ability are to be developed. The goal of this project is to explore and describe further possible applications of these models and to develop recommendations for their use.

Relevant publications:

Volkmer, S., Wetzel, N., Widmann, A., & Scharf, F. (2022). Attentional control in middle childhood is highly dynamic - Strong initial distraction is followed by advanced attention control. Developmental Science.

Wetzel, N., Widmann, A., & Scharf, F. (2021). Distraction of attention by novel sounds in children declines fast. Scientific Reports, 11(1), 5308.

Wetzel, N., Scharf, F., & Widmann, A. (2019). Can't Ignore-Distraction by Task-Irrelevant Sounds in Early and Middle Childhood. Child Development, 90(6), 454-464.