Frank Rijmen

Contact information

Research interests

• Componential psychometrics
• Nonlinear mixed models

Publications

Group by: Type / Year & Type

2008

International journal articles

• Kuppens, P., Van Mechelen, I., & Rijmen, F. (2008). Toward disentangling sources of individual differences in appraisal and anger. Journal of Personality, 76, 969-1000. doi:10.1111/j.1467-6494.2008.00511.x
• Rijmen, F., Vansteelandt, K., & De Boeck, P. (2008). Latent class models for diary method data: Parameter estimation by local computations. Psychometrika, 73, 167-182. doi:10.1007/s11336-007-9001-8
• Rijmen, F., & Vomlel, J. (2008). Assessing the performance of variational methods for mixed logistic regression models. Journal of Statistical Computation and Simulation, 78, 765-779. doi:10.1080/00949650701282507

2007

Chapters in books

• Rijmen, F., Tuerlinckx, F., Meulders, M., Smits, D. J. M., & Balázs, K. (2007). Mixed model estimation methods for item response models. In E. V. Smith & R. M. Smith (Eds.), Rasch measurement: Advanced and specialized applications. Maple Grove, MN: JAM Press.

2006

International journal articles

• Tuerlinckx, F., Rijmen, F., Verbeke, G., & De Boeck, P. (2006). Statistical inference in generalized linear mixed models: A review. British Journal of Mathematical & Statistical Psychology, 59, 225-255. doi:10.1348/000711005X79857

2005

International journal articles

• Rijmen, F., & De Boeck, P. (2005). A relation between a between-item multidimensional IRT model and the mixture Rasch model. Psychometrika, 70, 481-496. doi:10.1007/s11336-002-1007-7
• Rijmen, F., De Boeck, P., & van der Maas, H. L. J. (2005). An IRT model with a parameter-driven process for change. Psychometrika, 70, 651-669. doi:10.1007/s11336-002-1047-z
• Rijmen, F., Tuerlinckx, F., Meulders, M., Smits, D. J. M., & Balázs, K. (2005). Mixed model estimation methods for the Rasch model. Journal of Applied Measurement, 6, 273-288.

2004

Chapters in books

• Rijmen, F., & Briggs, D. (2004). Multidimensional person variance and latent item predictors. In P. De Boeck & M. Wilson (Eds.), Explanatory item response models: A generalized linear and nonlinear approach (pp. 247-265). New York: Springer.
• Tuerlinckx, F., Rijmen, F., Molenberghs, G., Verbeke, G., Briggs, D., Van den Noortgate, W., Meulders, M., & De Boeck, P. (2004). Estimation and software. In P. De Boeck & M. Wilson (Eds.), Explanatory item response models: A generalized linear and nonlinear approach (pp. 343-373). New York: Springer.

2003

International journal articles

• Rijmen, F., & De Boeck, P. (2003). A latent class model for individual differences in the interpretation of conditionals. Psychological Research, 67, 219-231. doi:10.1007/s00426-002-0092-7
• Rijmen, F., Tuerlinckx, F., De Boeck, P., & Kuppens, P. (2003). A nonlinear mixed model framework for item response theory. Psychological Methods, 8, 185-205. doi:10.1037/1082-989X.8.2.185

2002

International journal articles

• Rijmen, F., & De Boeck, P. (2002). The random weights linear logistic test model. Applied Psychological Measurement, 26, 271-285. doi:10.1177/0146621602026003003

2001

International journal articles

• Rijmen, F., & De Boeck, P. (2001). Propositional reasoning: The differential contribution of 'rules' to the difficulty of complex reasoning problems. Memory & Cognition, 29, 165-175.