The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Bias in Cross-Sectional Analyses of Longitudinal Mediation: Partial and Complete Mediation Under an Autoregressive Model
Open accessAbstract
Maxwell and Cole (2007) showed that cross-sectional approaches to mediation typically generate substantially biased estimates of longitudinal parameters in the special case of complete mediation. However, their results did not apply to the more typical case of partial mediation. We extend their previous work by showing that substantial bias can also occur with partial mediation. In particular, cross-sectional analyses can imply the existence of a substantial indirect effect even when the true longitudinal indirect effect is zero. Thus, a variable that is found to be a strong mediator in a cross-sectional analysis may not be a mediator at all in a longitudinal analysis. In addition, we show that very different combinations of longitudinal parameter values can lead to essentially identical cross-sectional correlations, raising serious questions about the interpretability of cross-sectional mediation data. More generally, researchers are encouraged to consider a wide variety of possible mediation models beyond simple cross-sectional models, including but not restricted to autoregressive models of change.
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SPSS and SAS procedures for estimating indirect effects in simple mediation models
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Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653
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Cited by
An index and test of linear moderated mediation
Hayes, A. F. (2015) · Multivariate Behavioral Research · doi:10.1080/00273171.2014.962683 · Cited by 3,979
Exploring pathways linking greenspace to health: theoretical and methodological guidance
Markevych, I., Schoierer, J., Hartig, T., Chudnovsky, A., Hystad, P., Dzhambov, A. M., de Vries, S., Triguero-Mas, M., Brauer, M., Nieuwenhuijsen, M. J., et al. (2017) · Environmental Research · doi:10.1016/j.envres.2017.06.028 · Cited by 2,543
Mendelian randomisation for mediation analysis: current methods and challenges for implementation
Carter, A. R., Sanderson, E., Hammerton, G., Richmond, R. C., Davey Smith, G., Heron, J., Taylor, A. E., Davies, N. M., & Howe, L. D. (2021) · European Journal of Epidemiology · doi:10.1007/s10654-021-00757-1 · Cited by 1,215
Gil de Zúñiga, H., Weeks, B., & Ardèvol-Abreu, A. (2017) · Journal of Computer-Mediated Communication · doi:10.1111/jcc4.12185 · Cited by 594
Cross-Sectional Analysis of Longitudinal Mediation Processes
O'Laughlin, K. D., Martin, M. J., & Ferrer, E. (2018) · Multivariate Behavioral Research · doi:10.1080/00273171.2018.1454822 · Cited by 475
Metadata
- Authors
- Maxwell, S. E., Cole, D. A., & Mitchell, M. A.
- Venue
- Multivariate Behavioral Research
- Publisher
- Informa UK Limited
- Published
- 2011-09-30
- Volume
- 46
- Issue
- 5
- Pages
- 816-841
- ISSN
- 0027-3171 (ISSN-L)
- 1532-7906
- OpenAlex
- W2119963803
- Cited by
- 1,338
- References
- 19
- FWCI
- 16.69
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Maxwell, S. E., Cole, D. A., & Mitchell, M. A. (2011). Bias in Cross-Sectional Analyses of Longitudinal Mediation: Partial and Complete Mediation Under an Autoregressive Model. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2011.606716
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
