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Speaker: Sonya Sterba

Psychologists are increasingly using model selection strategies to decide among competing models, rather than evaluating the fit of a given model in isolation. However, such interest in model selection outpaces an awareness that one or a few cases can have disproportionate impact on the model ranking. Though case influence on the fit of a single model in isolation has been often studied, case influence on model selection results is greatly underappreciated in psychology. Sterba and Pek (2012) introduced the issue of case influence on model selection and proposed three influence diagnostics for commonly used selection indices. The interpretation and behavior of these diagnostics will be discussed and illustrative examples will be presented. An awareness of how cases influence model selection results is shown to aid researchers in understanding how representative their sample level results are at the case level.

Hosted by: Psychology & Human Development Department