1.

Record Nr.

UNINA9910784438003321

Autore

Frees Edward W.

Titolo

Longitudinal and panel data : analysis and applications in the social sciences / / Edward W. Frees

Pubbl/distr/stampa

Cambridge : , : Cambridge University Press, , 2004

ISBN

1-107-14754-9

1-280-54050-8

0-511-79092-9

0-511-21527-4

0-511-21706-4

0-511-21169-4

0-511-31569-4

0-511-21346-8

Descrizione fisica

1 online resource (xvi, 467 pages) : illustrations; digital, PDF file(s)

Disciplina

300/.72/7

Soggetti

Social sciences - Research - Statistical methods

Longitudinal method

Panel analysis

Social sciences - Mathematical models

Social sciences - Statistical methods

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliography and index.

Nota di contenuto

Cover; Half-title; Title; Copyright; 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

Sommario/riassunto

This focuses on models and data that arise from repeated observations



of a cross-section of individuals, households or companies. These models have found important applications within business, economics, education, political science and other social science disciplines. The author introduces the foundations of longitudinal and panel data analysis at a level suitable for quantitatively oriented graduate social science students as well as individual researchers. He emphasizes mathematical and statistical fundamentals but also describes substantive applications from across the social sciences, showing the breadth and scope that these models enjoy.  The applications are enhanced by real-world data sets and software programs in SAS and Stata.