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European Conference on Personality

Thursday – 08-08-2024

04:15 pm

iCal
Prof. Richard E. Lucas | Michigan State University | United States

Dr. Thomas Gfrörer | University of Tübingen | Germany

Prof. Dr. Oliver Lüdtke | IPN – Leibniz Institute for Science and Mathematics Education | Germany

Jana Instinske | University of Bremen | Germany

Jeroen D. Mulder | Utrecht University | Netherlands

How, When, and Why (Not) Using Cross-Lagged Panel Models? Different Perspectives and Various Alternatives

Chair(s)
Jana Instinske (University of Bremen)

Co-chair(s) Prof. Dr. Christian Kandler (University of Bremen)

Co-chair(s) Prof. Dr. Christian Kandler (University of Bremen)

Room:
1102

Topic:
Personality Assessment, Methods and Statistics

Form of presentation:
Symposium

Duration:
90 Minutes

Cross-lagged panel models (CLPMs) are subject to several concerns regarding their appropriateness for examining direction of prediction between variables. Hence, various alternative models have been proposed – that also did not remain without criticism. In this symposium, we take up existing controversies: Different perspectives on modelling approaches of panel data are discussed in terms of which (causal) inferences they allow to be drawn considering their limitations. Lucas talks about the consideration of state components in CLPM approaches when aiming at investigating causal associations. Gfrörer shows impacts that not appropriately modelled time-invariant confounders have for the allegedly causal estimates. Lüdtke compares the CLPM to the alternative random-intercept CLPM focusing on differences regarding underlying assumptions and conclusions enabled. Instinske proposes an approach to disclose the directionality between different relatively stable personality characteristics. Mulder introduces the potential outcome approach as an alternative strategy for examining causal questions. The symposium closes with a general discussion.

04:15 pm

Is Stable-Trait Variance the Only Problem? The Importance of Modeling State Variance in Cross-Lagged Models

04:30 pm

Thinking clearly about time-invariant confounders in cross-lagged panel models: A guide for choosing a statistical model from a causal inference perspective

04:45 pm

A comparison of different approaches for estimating cross-lagged effects with panel data

05:00 pm

Another Modelling Approach to Examine the Directionality of Effects Between Personality Characteristics

05:15 pm

The potential outcomes approach to causal inference: An introduction for psychologists familiar with cross-lagged panel modeling