Anesthesia, critical care, perioperative, and pain research often involves study designs in
which the same outcome variable is repeatedly measured or observed over time on the …

Geometric morphometrics—a set of methods for the statistical analysis of shape once
saluted as a revolutionary advancement in the analysis of morphology—is now mature and …

Longitudinal experiments often involve multiple outcomes measured repeatedly within a set
of study participants. While many questions can be answered by modeling the various …

Longitudinal studies often incur several problems that challenge standard statistical
methods for data analysis. These problems include non-ignorable missing data in …

Covariance pattern mixture models for the analysis of multivariate heterogeneous longitudinal
data Page 1 The Annals of Applied Statistics 2015, Vol. 9, No. 2, 777–800 DOI …

In many applications of multivariate longitudinal mixed models, it is reasonable to assume
that each response is informed by only a subset of covariates. Moreover, one or more …

The variability of corneal OCT speckle statistics is indirectly related to changes in corneal
microstructure, which may be induced by intraocular pressure (IOP). A new approach is …

Functional magnetic resonance imaging (fMRI) investigations of a longitudinal nature, where
participants are scanned repeatedly over time and imaging data are obtained at more than …

Joint modelling techniques have seen great advances in the recent years, with several types
of joint models having been developed in literature that can handle a wide range of …

Impairment caused by Parkinson's disease (PD) is multidimensional (eg, sensoria, functions,
and cognition) and progressive. Its multidimensional nature precludes a single outcome to …