Explicit Causal Inference in Personality Research (ECIP)

• Applicant: Professor Dr. Michael Paul Grosz
• Subject Area: Personality Psychology, Clinical and Medical Psychology, Methodology
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 461127198

Causal inference is a central goal of science. The preferred method for studying causal effects are experiments. Yet, experiments are often unethical, unfeasible, or very costly in research on personality. Personality researchers have thus rarely applied experimental designs to estimate the causal effects. Causal inference is also possible in nonexperimental studies. However, explicit causal inference on the basis of nonexperimental data has been avoided in personality psychology due to the widespread belief that causal inference is only possible when experimental data are used. Hence, knowledge about causal effects and mechanisms tends to grow at a very slow pace, if at all, in research on personality. This is unfortunate because the shortage of empirical research on causal effects and mechanisms entails a divergence between empirical findings and theories given that theories are usually concerned with causal effects and mechanisms. The shortage of empirical research on causal effects furthermore limits the relevance of personality research for policymakers because knowledge about causal effects is necessary for designing effective and purposive policy interventions, regulations, and laws. The scientific network will promote personality research on causal effects. To do so, we will elaborate on, apply, and demonstrate methods for drawing causal inferences in empirical research on personality. The network will address methodological and conceptual issues surrounding causal inference in personality research by developing methodological/conceptual guidelines and an integrative framework. Furthermore, we will showcase feasible ways to draw explicit causal inferences in personality science by composing empirical studies and grant proposals. By demonstrating how personality researchers can effectively integrate causality into their work, the scientific network will help to reduce the divergence between theory and empirical evidence in research on personality and increase the relevance of personality science for policymakers.

• DFG Programme: Scientific Networks