Dr. Christian Geiser's Featured Publication Spotlight
Geiser, C. (2020). Longitudinal structural equation modeling with Mplus: A latent state-trait perspective. New York: Guilford.
What is the purpose of the book?
I wrote this book to teach investigators and students how to perform various longitudinal analyses using a software program called Mplus. This work is the result of many years of teaching longitudinal structural equation modeling as well as conducting research on longitudinal models. I'm very proud of it because it describes a complex family of statistics and complex software in a way that is clear and accessible, even for people with a basic statistical background.
The book will enable researchers to perform their analyses using techniques such as growth curve modeling, dynamic structural equation modeling, and planned missing data designs. In a step-by-step fashion, I guide them through the entire analytic process. All of this is framed within a latent state-trait (LST) framework, which gives scientists a sound theory from which to specify and test their models. Readers have commented that they have found the book to inspire new research questions in their line of work. This is one of the greatest joys of being a quantitative psychologist: to help other scientists to push their research agendas in new and exciting directions.
Who can benefit from the book?
The book is appropriate for anyone interested in longitudinal research. That is virtually everyone! Longitudinal research is the hallmark tool through which we answer questions about how people change over time as well as causal effects. I expect that the book will impact research in wide-ranging fields as psychology, education, medicine, and public health.
Where can researchers find the book?