- Oxford Library of Psychology
- [UNTITLED]
- Oxford Library of Psychology
- About the Editor
- Contributors
- Introduction
- Overview of Traditional/Classical Statistical Approaches
- Generalized Linear Models
- Categorical Methods
- Configural Frequency Analysis
- Nonparametric Statistical Techniques
- Correspondence Analysis
- Spatial Analysis
- Analysis of Imaging Data
- Twin Studies and Behavior Genetics
- Quantitative Analysis of Genes
- Multidimensional Scaling
- Latent Variable Measurement Models
- Multilevel Regression and Multilevel Structural Equation Modeling
- Structural Equation Models
- Developments in Mediation Analysis
- Moderation
- Longitudinal Data Analysis
- Dynamical Systems and Models of Continuous Time
- Intensive Longitudinal Data
- Dynamic Factor Analysis: Modeling Person-Specific Process
- Time Series Analysis
- Analyzing Event History Data
- Clustering and Classification
- Latent Class Analysis and Finite Mixture Modeling
- Taxometrics
- Missing Data Methods
- Secondary Data Analysis
- Data Mining
- Meta-Analysis and Quantitative Research Synthesis
- Common Fallacies in Quantitative Research Methodology
- Index
Abstract and Keywords
Modern data collection technologies are providing large data sets, with many repeated observations of many individuals on many variables—and new opportunities for application of analytical techniques that consider individuals as unique, complex, multivariate, dynamic entities. In this chapter we review the conceptual and technical background for dynamic factor analysis and provide a primer for application to multivariate time series data. Step-by-step procedures are illustrated using daily diary data obtained from three women over 100+ days. Specifically, we provide background on and demonstrate (1) formulation of DFA research questions; (2) study design and data collection; (3) variable selection and data pre-processing procedures; (4) the fitting and evaluation of person-specific DFA models; and (5) examination of between-person differences/similarities. We conclude by pointing to some extensions that might be elaborated and used to articulate additional complexities of within-person process.
Keywords: longitudinal, P-technique, dynamic systems, idiographic, ecological momentary assessment
Nilam Ram, Department of Human Development and Family Studies, Pennsylvania State University, University Park, PA and Max Plank Institute for Human Development, Berlin, Germany
Annette Brose, Max Plank Institute for Human Development and Max Plank Institute for Human Cognitive and Brain Sciences, Berlin, Germany
Peter C. M. Molenaar, Department of Human Development and Family Studies, Pennsylvania State University, University Park, PA
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- Oxford Library of Psychology
- [UNTITLED]
- Oxford Library of Psychology
- About the Editor
- Contributors
- Introduction
- Overview of Traditional/Classical Statistical Approaches
- Generalized Linear Models
- Categorical Methods
- Configural Frequency Analysis
- Nonparametric Statistical Techniques
- Correspondence Analysis
- Spatial Analysis
- Analysis of Imaging Data
- Twin Studies and Behavior Genetics
- Quantitative Analysis of Genes
- Multidimensional Scaling
- Latent Variable Measurement Models
- Multilevel Regression and Multilevel Structural Equation Modeling
- Structural Equation Models
- Developments in Mediation Analysis
- Moderation
- Longitudinal Data Analysis
- Dynamical Systems and Models of Continuous Time
- Intensive Longitudinal Data
- Dynamic Factor Analysis: Modeling Person-Specific Process
- Time Series Analysis
- Analyzing Event History Data
- Clustering and Classification
- Latent Class Analysis and Finite Mixture Modeling
- Taxometrics
- Missing Data Methods
- Secondary Data Analysis
- Data Mining
- Meta-Analysis and Quantitative Research Synthesis
- Common Fallacies in Quantitative Research Methodology
- Index
