Longitudinal data analysis
By Geert Molenberghs, Geert Verbeke. 2008
212 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/6566bbfed494572439fc8665770f7a47ee3f4a0b
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
- Philip Dawid
- Mohsen Pourahmadi
- Peter B. Imrey
- Joseph G. Ibrahim
- Geert Molenberghs
- Chandra R. Bhat
- Clifford Lam
- Geert Verbeke
In Statistics and Probability
- Joseph G. Ibrahim
- Mohsen Pourahmadi
- Geert Molenberghs
- Philip Dawid
- Peter B. Imrey
- Nicholas J. Horton
- Clifford Lam
- Aaron M. Christ
Citations in the corpus
- Covariance Estimation: The GLM and Regularization Perspectives (2011, methodology): “Parsimonious and accurate modeling of the covariance structure is important in these application areas (Cannon et al., 2001; Carroll, 2003; Fitzmaurice et al., 2009).”
- A Commentary on Statistical Assessment of Violence Recidivism Risk (2015, methodology): “ for individual risks. CM1’s and HC’s attempted condence intervals for individual risks are analogous to this latter aspect of modeling repeated measures binary data using mixed logistic regression (Fitzmaurice et al. 2008; Molenberghs and Verbeke 2005; Vonesh 2012), but dier in that elements of the”
- Missing data methods in longitudinal studies: a review (2009, background): “Another aspect of the problem, discussed by Henderson et al. (2000), Brown and Ibrahim (2003a, 2003b), Ibrahim et al.”