Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Fixed-Effects Models
- 3 Models with Random Effects
- 4 Prediction and Bayesian Inference
- 5 Multilevel Models
- 6 Stochastic Regressors
- 7 Modeling Issues
- 8 Dynamic Models
- 9 Binary Dependent Variables
- 10 Generalized Linear Models
- 11 Categorical Dependent Variables and Survival Models
- Appendix A Elements of Matrix Algebra
- Appendix B Normal Distribution
- Appendix C Likelihood-Based Inference
- Appendix D State Space Model and the Kalman Filter
- Appendix E Symbols and Notation
- Appendix F Selected Longitudinal and Panel Data Sets
- References
- Index
1 - Introduction
Published online by Cambridge University Press: 05 September 2012
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Fixed-Effects Models
- 3 Models with Random Effects
- 4 Prediction and Bayesian Inference
- 5 Multilevel Models
- 6 Stochastic Regressors
- 7 Modeling Issues
- 8 Dynamic Models
- 9 Binary Dependent Variables
- 10 Generalized Linear Models
- 11 Categorical Dependent Variables and Survival Models
- Appendix A Elements of Matrix Algebra
- Appendix B Normal Distribution
- Appendix C Likelihood-Based Inference
- Appendix D State Space Model and the Kalman Filter
- Appendix E Symbols and Notation
- Appendix F Selected Longitudinal and Panel Data Sets
- References
- Index
Summary
Abstract. This chapter introduces the many key features of the data and models used in the analysis of longitudinal and panel data. Here, longitudinal and panel data are defined and an indication of their widespread usage is given. The chapter discusses the benefits of these data; these include opportunities to study dynamic relationships while understanding, or at least accounting for, cross-sectional heterogeneity. Designing a longitudinal study does not come without a price; in particular, longitudinal data studies are sensitive to the problem of attrition, that is, unplanned exit from a study. This book focuses on models appropriate for the analysis of longitudinal and panel data; this introductory chapter outlines the set of models that will be considered in subsequent chapters.
What Are Longitudinal and Panel Data?
Statistical Modeling
Statistics is about data. It is the discipline concerned with the collection, summarization, and analysis of data to make statements about our world. When analysts collect data, they are really collecting information that is quantified, that is, transformed to a numerical scale. There are many well-understood rules for reducing data, using either numerical or graphical summary measures. These summary measures can then be linked to a theoretical representation, or model, of the data. With a model that is calibrated by data, statements about the world can be made.
As users, we identify a basic entity that we measure by collecting information on a numerical scale. This basic entity is our unit of analysis, also known as the research unit or observational unit.
- Type
- Chapter
- Information
- Longitudinal and Panel DataAnalysis and Applications in the Social Sciences, pp. 1 - 17Publisher: Cambridge University PressPrint publication year: 2004