Despite the recent surge in the development of powerful modeling strategies to test
questions about individual differences in stability and change over time, these methods are …

In the past two decades a parametric multivariate regression modelling approach for
analyzing growth curve data has achieved prominence. The approach, which has several …

In longitudinal studies it is often of interest to investigate how a marker that is repeatedly
measured in time is associated with a time to an event of interest, eg, prostate cancer studies …

Multilevel analysis is a methodology for the analysis of data with complex patterns of
variability, with a focus on nested sources of such variability–pupils in classes, employees in …

Many texts are excellent sources of knowledge about individual statistical tools, but the art of
data analysis is about choosing and using multiple tools. Instead of presenting isolated …

Data mining is the discovery of interesting, unexpected or valuable structures in large
datasets. As such, it has two rather different aspects. One of these concerns large …

Abstract Pediatric neuroimaging studies 1, 2, 3, 4, 5, up to now exclusively cross sectional,
identify linear decreases in cortical gray matter and increases in white matter across ages 4 …

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework
for statistical modelling, with an emphasis on numerical and graphical methods. This new …

Modelling Survival Data in Medical Research, Fourth Edition, describes the analysis of
survival data, illustrated using a wide range of examples from biomedical research. Written …

This book discusses the most important techniques available for longitudinal data analysis,
from simple techniques such as the paired t-test and summary statistics, to more …