Multiphase mixed-effects models for repeated measures data
By R. Cudeck, K. Klebe. 2002
70 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/cbb806963ed02a4fdeb0f7f4f9a5c2d407fed186
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
In Statistics and Probability
- Kevin J. Grimm
- K. Widaman
- J. Mcardle
- Lijuan Wang
- Satoshi Usami
- Chia-huei Wu
- E. Hamaker
- Jonathon R. B. Halbesleben
Citations in the corpus
- Five Steps in Latent Curve and Latent Change Score Modeling with Longitudinal Data (2010, methodology): “Additional nonlinear models, including multiphase ( Cudeck & Klebe, 2002 ) and structured curves (Browne & du Toit, 1991) can be fit to these data, but are not described here.”
- A Simulation Study Comparison of Bayesian Estimation With Conventional Methods for Estimating Unknown Change Points (2008, methodology): “…parameters for the linear phase, and one parameter for the change point location) to capture the change pattern, we adopted this restricted version of the model with four parameters to obtain a continuous change pattern and smooth transition before and after the change point (Cudeck & Klebe, 2002).”
- Residual Structures in Latent Growth Curve Modeling (2010, background): “For example, change during kindergarten might be fundamentally different from changes after kindergarten, so a spline or multiphase model (Cudeck & Klebe, 2002; Ram & Grimm, 2007) that allows for different phases of development might be more appropriate.”