Review of Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research
In: Structural equation modeling: a multidisciplinary journal, Band 26, Heft 3, S. 493-495
ISSN: 1532-8007
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In: Structural equation modeling: a multidisciplinary journal, Band 26, Heft 3, S. 493-495
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 19, Heft 1, S. 137-151
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 25, Heft 5, S. 824-828
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 25, Heft 4, S. 639-649
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 25, Heft 2, S. 167-178
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 24, Heft 2, S. 157-158
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 23, Heft 3, S. 466-475
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 16, Heft 4, S. 676-701
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, S. 1-12
ISSN: 1532-8007
In: Methodology in the social sciences
"Over the past 20 years, there has been an incredible change in the size, structure, and types of data collected in the social and behavioral sciences. Thus, social and behavioral researchers have increasingly been asking the question: "What do I do with all of this data?" The goal of this book is to help answer that question. It is our viewpoint that in social and behavioral research, to answer the question "What do I do with all of this data?", one needs to know the latest advances in the algorithms and think deeply about the interplay of statistical algorithms, data, and theory. An important distinction between this book and most other books in the area of machine learning is our focus on theory"--
In: Methodology in the social sciences
In: Methodology in the social sciences
"Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results."--Publisher description
In: Structural equation modeling: a multidisciplinary journal, Band 26, Heft 6, S. 924-930
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 26, Heft 4, S. 623-635
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 23, Heft 3, S. 354-367
ISSN: 1532-8007