Abstract
Cross-lagged panel models (CLPMs) are commonly used to estimate causal influences between two variables with repeated assessments. The lagged effects in a CLPM depend on the time interval between assessments, eventually becoming undetectable at longer intervals. To address this limitation, we incorporate instrumental variables (IVs) into the CLPM with two study waves and two variables. Doing so enables estimation of both the lagged (i.e., “distal”) effects and the bidirectional cross-sectional (i.e., “proximal”) effects at each wave. The distal effects reflect Granger-causal influences across time, which decay with increasing time intervals. The proximal effects capture causal influences that accrue over time and can help infer causality when the distal effects become undetectable at longer intervals. Significant proximal effects, with a negligible distal effect, would imply that the time interval is too long to estimate a lagged effect at that time interval using the standard CLPM. Through simulations and an empirical application, we demonstrate the impact of time intervals on causal inference in the CLPM and present modeling strategies to detect causal influences regardless of the time interval in a study. Furthermore, to motivate empirical applications of the proposed model, we highlight the utility and limitations of using genetic variables as IVs in large-scale panel studies.
Original language | English |
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Pages (from-to) | 342-370 |
Number of pages | 29 |
Journal | Multivariate Behavioral Research |
Volume | 59 |
Issue number | 2 |
Early online date | 15 Feb 2024 |
DOIs | |
Publication status | Published - 2024 |
Bibliographical note
Publisher Copyright:© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.
Funding
Funding: This work has been funded by the U.S. National Institutes of Health (NIH) grants R01DA049867 (MCN, CVD, HHMM, MS) and 5T32MH-020030 (LFSC). MCN was also supported by funds from the Rachel Brown Banks’ Chair of Psychiatry at Virginia Commonwealth University. DIB was supported by the Royal Netherlands Academy of Arts and Sciences (KNAW) Academy Professor Award (PAH/6635). ANTR Survey 8 was funded by ZonMW (Addiction) Project: 31160008 (PI: DIB). (ZonMW is a partnership between ZorgOnderzoek Nederland (Care Research Netherlands, Dutch abbreviation: ZON) and the Medical Sciences (Dutch abbreviation: MW) domain of the Dutch Research Council (NWO).) ANTR Survey 10 was funded by ERC (European Research Council) Starting Grant 284167 (PI: JMV).
Funders | Funder number |
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LFSC | |
National Institutes of Health | R01DA049867, 5T32MH-020030 |
Virginia Commonwealth University | |
European Research Council | 284167 |
Koninklijke Nederlandse Akademie van Wetenschappen | PAH/6635 |
ZONMW | 31160008 |
Keywords
- Causal inference
- CLPM
- instrumental variables
- lagged effects
Cohort Studies
- Netherlands Twin Register (NTR)