Longitudinal studies are on the rise, no doubt. Properly conducting longitudinal studies and then analyzing the data can be a complex undertaking. John McArdle and John Nesselroade focus on five basic questions that can be tackled with structural equation models, when analyzing longitudinal data:
- Direct identification of intraindividual changes.
- Direct identification of interindividual differences in intraindividual changes.
- Examining interrelationships in intraindividual changes.
- Analyses of causes (determinants) of intraindividual changes.
- Analyses of causes (determinants) of interindividual differences in intraindividual changes.
I find it especially noteworthy, that the authors put an emphasis on factorial invariance over time and latent change scores. In my view, this makes this book a must read to become a longitudinal data wizard.
Need another argument? Afraid of cumbersome mathematical language? Here is what the authors say about it: „We focus on the big picture approach rather than the algebraic details.“