Uncertainty in quantitative methods

How might quantitative research methods better incorporate uncertainty into their calculations? In collaboration with statisticians and other quantitative researchers, these publications extend structural equation modelling (SEM) in response to this question

References

Zyphur, M. J., Allison, P. D., Tay, L., Voelkle, M. C., Preacher, K. J., Zhang, Z., Hamaker, E. L., Shamsollahi, A., Pierides, D. C., Koval, P., & Diener, E. (2020). From Data to Causes I: Building A General Cross-Lagged Panel Model (GCLM). Organizational Research Methods, 23(4), 651-687.

Zyphur, M. J., Voelkle, M. C., Tay, L., Allison, P. D., Preacher, K. J., Zhang, Z., Hamaker, E. L., Shamsollahi, A., Pierides, D. C., Koval, P., & Diener, E. (2020). From Data to Causes II: Comparing Approaches to Panel Data Analysis. Organizational Research Methods, 23(4), 688-716.

Zyphur, M. J., Hamaker, E. L., Tay, L., Voelkle, M., Preacher, K. J., Zhang, Z., Allison, P. D., Pierides, D. C., Koval, P., & Diener, E. F. (2021). From Data to Causes III: Bayesian Priors for General Cross-Lagged Panel Models (GCLM). Frontiers in Psychology, 12(112).

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