Integrating Cross-Lagged Panel Models with Instrumental Variables to Extend the Temporal Generalizability of Causal Inference

Madhurbain Singha Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityCorrespondence[email protected]

https://orcid.org/0000-0002-9396-2860

Conor V. Dolanb Department of Biological Psychology, Vrije Universiteit Amsterdam

https://orcid.org/0000-0002-2496-8492

Michael C. Nealea Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University;b Department of Biological Psychology, Vrije Universiteit Amsterdam

https://orcid.org/0000-0003-4887-659X

References

Kuiper, R. M., & Ryan, O. (2018). Drawing conclusions from cross-lagged relationships: Re-considering the role of the time-interval. Structural Equation Modeling: A Multidisciplinary Journal, 25(5), 809–823. https://doi.org/10.1080/10705511.2018.1431046
Web of Science ®Google Scholar
Maydeu-Olivares, A., Shi, D., & Rosseel, Y. (2019). Instrumental variables two-stage least squares (2SLS) vs. maximum likelihood structural equation modeling of causal effects in linear regression models. Structural Equation Modeling: A Multidisciplinary Journal, 26(6), 876–892. https://doi.org/10.1080/10705511.2019.1607740
Web of Science ®Google Scholar

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Integrating Cross-Lagged Panel Models with Instrumental Variables to Extend the Temporal Generalizability of Causal Inference

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