SELECTED Publications
Data and preprints are linked where available; if no preprint is linked, please contact us for a copy.
Submitted manuscripts:
van Bork, R. Marsman, M., Rhemtulla, M., Epskamp, S., Kruis, J., & Borsboom, D. (under review). Common effect models: Positive or negative manifold?
Wang, Y. A., & Rhemtulla, M. (under revision). Power analysis for parameter estimation in structural equation
modeling: A discussion and tutorial. Advances in Methods and Practices for Psychological Science.
de Bolt, M. C.*, Rhemtulla, M., & Oakes, L. M. (under revision). Robust data and power in infant
looking time research: Number of infants and number of trials. Infancy
Wysocki, A., & Rhemtulla, M. (under revision). On penalty parameter selection for estimating network models. Multivariate Behavioral Research.
van Bork, R., Rhemtulla, M., Waldorp, L., Kruis, J., Rezvanifar, S., & Borsboom, D. (under revision). Latent variable models and networks: Statistical equivalence and testability. Multivariate Behavioral Research.
Published / In press :
Rhemtulla, M., van Bork, R., & Borsboom, D. (in press). Worse than measurement error: Consequences of inappropriate latent variable models. Psychological Methods. preprint
Williams, D., Rhemtulla, M., Wysocki, A., & Rast, P. (in press). On Non-Regularized Estimation of Psychological Networks. Multivariate Behavioral Research. preprint
Schott, E., Rhemtulla, M., & Byers-Heinlein, K. (2019). Should I test more babies? Solutions for transparent data peeking. Infant Behavior and Development, 54, 166-176. preprint
van Bork, R., Wijsen, L., & Rhemtulla, M. (in press). Toward a causal interpretation of the common factor model. Disputatio.
Borsboom, D., Robinaugh, D. J., The Psychosystems Group, Rhemtulla, M., & Cramer, A. O. J. (2018). Robustness and replicability of psychopathology networks. World Psychiatry, 17, 143-144.
Savalei, V., & Rhemtulla, M. (2017). Normal theory two-stage estimator for models with composites when data are missing at the item level. Journal of Educational and Behavioral Statistics, 42, 405-431. pdf data
van Bork, R., Epskamp, S., Rhemtulla, M., Borsboom, D., & van der Maas, H. L. J. (2017). What is the p=factor of psychopathology? Some risks of general factor modeling. Theory and Psychology, 27, 759-773. pdf
Savalei, V., & Rhemtulla, M. (2017). Normal theory GLS estimator for missing data: An application to item-level missing data and a comparison to two-stage ML. Frontiers in Psychology, 8:767.
Epskamp, S., Rhemtulla, M., & Borsboom, D. (2017). Generalized network psychometrics: Combining network and latent variable models. Psychometrika, 82 (4), 904-927. arXiv
Rhemtulla, M., & Hancock, D. (2016). Planned missing data designs for educational research. Educational Psychologist, 51, 305-316. pdf
van Bork, R., Rhemtulla, M., & Borsboom, D. (2016). Composites can be causal too. Comment on Möttus (2016). European Journal of Personality, 30, 304-340. pdf
Rhemtulla, M. (2016). Population performance of SEM parceling strategies under measurement and structural model misspecification. Psychological Methods, 21, 348-368. pdf
Borsboom, D., Rhemtulla, M., Dolan, C., Cramer, A. O. J., Scheffer, M., & van der Maas, H. L. J. (2016). Kinds versus continua: A review of psychometric approaches to uncover the structure of psychiatric constructs. Psychological Medicine, 46, 1567-1579.
Rhemtulla, M., Fried, E. I., Aggen, S. H., Tuerlinckx, F., Kendler, K., & Borsboom, D. (2016). Network analysis of substance abuse and dependence symptoms. Drug and Alcohol Dependence, 161, 230-237. http://dx.doi.org/10.1016/j.drugalcdep.2016.02.005 pdf
Rhemtulla, M., van Bork, R., & Borsboom, D. (2015). Calling models with causal indicators measurement models implies more than they can deliver. Measurement, 13, 59-62. pdf
Rhemtulla, M., Savalei, V., & Little, T. D. (2016). On the asymptotic relative efficiency of planned missingness designs. Psychometrika, 81, 60-89. pdf
Rhemtulla, M., Jia, F., Wu, W., & Little, T. D. (2014). Planned missing designs to optimize the efficiency of latent growth parameter estimates. International Journal of Behavioral Development, 38, 5, 423-434. pdf
Savalei, V., & Rhemtulla, M. (2013). The performance of robust test statistics with categorical data. British Journal of Mathematical and Statistical Psychology, 66, 201-223. pdf
Rhemtulla, M., & Little, T. D. (2012). Planned missing data designs for research in cognitive development. Journal of Cognition and Development, 13, 425-438. pdf
Rhemtulla, M., Brosseau-Liard, P., & Savalei, V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under sub-optimal conditions. Psychological Methods, 17, 354-373. pdf
Savalei, V., & Rhemtulla, M. (2012). Teachers Corner: On obtaining estimates of the fraction of missing information from FIML. Structural Equation Modeling, 19, 477-494. pdf
Rhemtulla, M., & Tucker-Drob, E. M. (2012). Gene-by-socioeconomic status interaction on school readiness. Behavior Genetics, 42, 549-558. pdf
Rhemtulla, M., & Tucker-Drob, E. M. (2011). Correlated longitudinal changes across linguistic, achievement, and psychomotor domains in early childhood: Evidence for a global dimension of development. Developmental Science, 14, 1245-1254. pdf
Conference Presentations
Wysocki, A. C. & Rhemtulla, M. On penalty parameter selection for estimating network models. Paper presented at International Meetings of the Psychometric Society. New York, New York. Powerpoint
Wysocki, A. C., Williams, D. R., & Rhemtulla, M. (2018). On selection methods in network models. Poster presented at Association for Psychological Science Conference. San Francisco, California.
van Bork, R. Marsman, M., Rhemtulla, M., Epskamp, S., Kruis, J., & Borsboom, D. (under review). Common effect models: Positive or negative manifold?
Wang, Y. A., & Rhemtulla, M. (under revision). Power analysis for parameter estimation in structural equation
modeling: A discussion and tutorial. Advances in Methods and Practices for Psychological Science.
de Bolt, M. C.*, Rhemtulla, M., & Oakes, L. M. (under revision). Robust data and power in infant
looking time research: Number of infants and number of trials. Infancy
Wysocki, A., & Rhemtulla, M. (under revision). On penalty parameter selection for estimating network models. Multivariate Behavioral Research.
van Bork, R., Rhemtulla, M., Waldorp, L., Kruis, J., Rezvanifar, S., & Borsboom, D. (under revision). Latent variable models and networks: Statistical equivalence and testability. Multivariate Behavioral Research.
Published / In press :
Rhemtulla, M., van Bork, R., & Borsboom, D. (in press). Worse than measurement error: Consequences of inappropriate latent variable models. Psychological Methods. preprint
Williams, D., Rhemtulla, M., Wysocki, A., & Rast, P. (in press). On Non-Regularized Estimation of Psychological Networks. Multivariate Behavioral Research. preprint
Schott, E., Rhemtulla, M., & Byers-Heinlein, K. (2019). Should I test more babies? Solutions for transparent data peeking. Infant Behavior and Development, 54, 166-176. preprint
van Bork, R., Wijsen, L., & Rhemtulla, M. (in press). Toward a causal interpretation of the common factor model. Disputatio.
Borsboom, D., Robinaugh, D. J., The Psychosystems Group, Rhemtulla, M., & Cramer, A. O. J. (2018). Robustness and replicability of psychopathology networks. World Psychiatry, 17, 143-144.
Savalei, V., & Rhemtulla, M. (2017). Normal theory two-stage estimator for models with composites when data are missing at the item level. Journal of Educational and Behavioral Statistics, 42, 405-431. pdf data
van Bork, R., Epskamp, S., Rhemtulla, M., Borsboom, D., & van der Maas, H. L. J. (2017). What is the p=factor of psychopathology? Some risks of general factor modeling. Theory and Psychology, 27, 759-773. pdf
Savalei, V., & Rhemtulla, M. (2017). Normal theory GLS estimator for missing data: An application to item-level missing data and a comparison to two-stage ML. Frontiers in Psychology, 8:767.
Epskamp, S., Rhemtulla, M., & Borsboom, D. (2017). Generalized network psychometrics: Combining network and latent variable models. Psychometrika, 82 (4), 904-927. arXiv
Rhemtulla, M., & Hancock, D. (2016). Planned missing data designs for educational research. Educational Psychologist, 51, 305-316. pdf
van Bork, R., Rhemtulla, M., & Borsboom, D. (2016). Composites can be causal too. Comment on Möttus (2016). European Journal of Personality, 30, 304-340. pdf
Rhemtulla, M. (2016). Population performance of SEM parceling strategies under measurement and structural model misspecification. Psychological Methods, 21, 348-368. pdf
Borsboom, D., Rhemtulla, M., Dolan, C., Cramer, A. O. J., Scheffer, M., & van der Maas, H. L. J. (2016). Kinds versus continua: A review of psychometric approaches to uncover the structure of psychiatric constructs. Psychological Medicine, 46, 1567-1579.
Rhemtulla, M., Fried, E. I., Aggen, S. H., Tuerlinckx, F., Kendler, K., & Borsboom, D. (2016). Network analysis of substance abuse and dependence symptoms. Drug and Alcohol Dependence, 161, 230-237. http://dx.doi.org/10.1016/j.drugalcdep.2016.02.005 pdf
Rhemtulla, M., van Bork, R., & Borsboom, D. (2015). Calling models with causal indicators measurement models implies more than they can deliver. Measurement, 13, 59-62. pdf
Rhemtulla, M., Savalei, V., & Little, T. D. (2016). On the asymptotic relative efficiency of planned missingness designs. Psychometrika, 81, 60-89. pdf
Rhemtulla, M., Jia, F., Wu, W., & Little, T. D. (2014). Planned missing designs to optimize the efficiency of latent growth parameter estimates. International Journal of Behavioral Development, 38, 5, 423-434. pdf
Savalei, V., & Rhemtulla, M. (2013). The performance of robust test statistics with categorical data. British Journal of Mathematical and Statistical Psychology, 66, 201-223. pdf
Rhemtulla, M., & Little, T. D. (2012). Planned missing data designs for research in cognitive development. Journal of Cognition and Development, 13, 425-438. pdf
Rhemtulla, M., Brosseau-Liard, P., & Savalei, V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under sub-optimal conditions. Psychological Methods, 17, 354-373. pdf
Savalei, V., & Rhemtulla, M. (2012). Teachers Corner: On obtaining estimates of the fraction of missing information from FIML. Structural Equation Modeling, 19, 477-494. pdf
Rhemtulla, M., & Tucker-Drob, E. M. (2012). Gene-by-socioeconomic status interaction on school readiness. Behavior Genetics, 42, 549-558. pdf
Rhemtulla, M., & Tucker-Drob, E. M. (2011). Correlated longitudinal changes across linguistic, achievement, and psychomotor domains in early childhood: Evidence for a global dimension of development. Developmental Science, 14, 1245-1254. pdf
Conference Presentations
Wysocki, A. C. & Rhemtulla, M. On penalty parameter selection for estimating network models. Paper presented at International Meetings of the Psychometric Society. New York, New York. Powerpoint
Wysocki, A. C., Williams, D. R., & Rhemtulla, M. (2018). On selection methods in network models. Poster presented at Association for Psychological Science Conference. San Francisco, California.