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Longitudinal and panel data : analysis and applications in the social sciences / / Edward W. Frees [[electronic resource]]
Longitudinal and panel data : analysis and applications in the social sciences / / Edward W. Frees [[electronic resource]]
Autore Frees Edward W.
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2004
Descrizione fisica 1 online resource (xvi, 467 pages) : digital, PDF file(s)
Disciplina 300/.72/7
Soggetto topico Social sciences - Research - Statistical methods
Longitudinal method
Panel analysis
Social sciences - Mathematical models
Social sciences - Statistical methods
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
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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 SetsReferences; Index
Altri titoli varianti Longitudinal & Panel Data
Record Nr. UNINA-9910458150503321
Frees Edward W.  
Cambridge : , : Cambridge University Press, , 2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Longitudinal and panel data : analysis and applications in the social sciences / / Edward W. Frees
Longitudinal and panel data : analysis and applications in the social sciences / / Edward W. Frees
Autore Frees Edward W.
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2004
Descrizione fisica 1 online resource (xvi, 467 pages) : illustrations; digital, PDF file(s)
Disciplina 300/.72/7
Soggetto topico Social sciences - Research - Statistical methods
Longitudinal method
Panel analysis
Social sciences - Mathematical models
Social sciences - Statistical methods
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
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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
Altri titoli varianti Longitudinal & Panel Data
Record Nr. UNINA-9910784438003321
Frees Edward W.  
Cambridge : , : Cambridge University Press, , 2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Models for intensive longitudinal data [[electronic resource] /] / edited by Theodore A. Walls and Joseph L. Schafer
Models for intensive longitudinal data [[electronic resource] /] / edited by Theodore A. Walls and Joseph L. Schafer
Pubbl/distr/stampa Oxford ; ; New York, : Oxford University Press, 2006
Descrizione fisica 1 online resource (311 p.)
Disciplina 300/.72/7
Altri autori (Persone) WallsTheodore A
SchaferJ. L (Joseph L.)
Soggetto topico Social sciences - Research - Statistical methods
Social sciences
Longitudinal method
Soggetto genere / forma Electronic books.
ISBN 0-19-803866-6
1-280-55918-7
1-4294-0521-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Contents; Contributors; Introduction: Intensive Longitudinal Data; 1 Multilevel Models for Intensive Longitudinal Data; 1.1 Behavioral Scientific Motivations for Collecting Intensive Longitudinal Data; 1.2 Overview of Multilevel Models; 1.3 Applying Multilevel Modeling to Intensive Longitudinal Data; 1.4 Application: Control and Choice in Indian Schoolchildren; 1.5 Summary; 2 Marginal Modeling of Intensive Longitudinal Data by Generalized Estimating Equations; 2.1 What Is GEE Regression?; 2.2 Practical Considerations in the Application of GEE
2.3 Application: Reanalysis of the Control and Choice Data Using GEE3 A Local Linear Estimation Procedure for Functional Multilevel Modeling; 3.1 The Model; 3.2 Practical Considerations; 3.3 Application: Smoking Cessation Study; 3.4 Discussion; 4 Application of Item Response Theory Models for Intensive Longitudinal Data; 4.1 IRT Model; 4.2 Estimation; 4.3 Application: Adolescent Smoking Study; 4.4 Discussion; 5 Fitting Curves with Periodic and Nonperiodic Trends and Their Interactions with Intensive Longitudinal Data; 5.1 Periodic and Nonperiodic Trends; 5.2 The Model
5.3 Application: Personality Data5.4 Discussion; 6 Multilevel Autoregressive Modeling of Interindividual Differences in the Stability of a Process; 6.1 Defining Stability as Regularity in a Time Series; 6.2 Multilevel Models; 6.3 A Multilevel AR(1) Model; 6.4 Application: Daily Alcohol Use; 6.5 Estimating This Model in SAS PROC MIXED; 6.6 Predicting the Individual AR(1) Coefficients; 6.7 Discussion; 7 The State-Space Approach to Modeling Dynamic Processes; 7.1 Gaussian State-Space Models; 7.2 Some Special Cases of State-Space Models; 7.3 Parameter Estimation
7.4 Application 1: Connectivity Analysis with fMRI Data7.5 Application 2: Testing the Induced Demand Hypothesis from Matched Traffic Profiles; 7.6 Conclusions; 8 The Control of Behavioral Input/Output Systems; 8.1 A Typical Input/Output System; 8.2 Modeling System Dynamics; 8.3 Controller Strategies to Meet an Output Target; 8.4 Fitting Dynamic Models to Intensive Longitudinal Data; 9 Dynamical Systems Modeling: An Application to the Regulation of Intimacy and Disclosure in Marriage; 9.1 Self-Regulation and Intrinsic Dynamics; 9.2 Coupled Regulation and Coupled Dynamics
9.3 Time-Delay Embedding9.4 Accounting for Individual Differences in Dynamics; 9.5 Application: Daily Intimacy and Disclosure in Married Couples; 9.6 Discussion; 10 Point Process Models for Event History Data: Applications in Behavioral Science; 10.1 Ecological Momentary Assessment of Smoking; 10.2 Point Process Models; 10.3 Application: An EMA Study of Smoking Data; 10.4 Discussion of Results; 10.5 Multivariate Point Patterns; 11 Emerging Technologies and Next-Generation Intensive Longitudinal Data Collection; 11.1 Intensive Data Collection Systems
11.2 Statistical Issues for Intensive Longitudinal Measurement
Record Nr. UNINA-9910465141603321
Oxford ; ; New York, : Oxford University Press, 2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Models for intensive longitudinal data / / edited by Theodore A. Walls and Joseph L. Schafer
Models for intensive longitudinal data / / edited by Theodore A. Walls and Joseph L. Schafer
Pubbl/distr/stampa Oxford ; ; New York, : Oxford University Press, 2006
Descrizione fisica 1 online resource (311 pages)
Disciplina 300/.72/7
Altri autori (Persone) WallsTheodore A
SchaferJ. L (Joseph L.)
Soggetto topico Social sciences - Research - Statistical methods
Social sciences
Longitudinal method
ISBN 0-19-803866-6
1-280-55918-7
1-4294-0521-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Contents; Contributors; Introduction: Intensive Longitudinal Data; 1 Multilevel Models for Intensive Longitudinal Data; 1.1 Behavioral Scientific Motivations for Collecting Intensive Longitudinal Data; 1.2 Overview of Multilevel Models; 1.3 Applying Multilevel Modeling to Intensive Longitudinal Data; 1.4 Application: Control and Choice in Indian Schoolchildren; 1.5 Summary; 2 Marginal Modeling of Intensive Longitudinal Data by Generalized Estimating Equations; 2.1 What Is GEE Regression?; 2.2 Practical Considerations in the Application of GEE
2.3 Application: Reanalysis of the Control and Choice Data Using GEE; 3 A Local Linear Estimation Procedure for Functional Multilevel Modeling; 3.1 The Model; 3.2 Practical Considerations; 3.3 Application: Smoking Cessation Study; 3.4 Discussion; 4 Application of Item Response Theory Models for Intensive Longitudinal Data; 4.1 IRT Model; 4.2 Estimation; 4.3 Application: Adolescent Smoking Study; 4.4 Discussion; 5 Fitting Curves with Periodic and Nonperiodic Trends and Their Interactions with Intensive Longitudinal Data; 5.1 Periodic and Nonperiodic Trends; 5.2 The Model
5.3 Application: Personality Data; 5.4 Discussion; 6 Multilevel Autoregressive Modeling of Interindividual Differences in the Stability of a Process; 6.1 Defining Stability as Regularity in a Time Series; 6.2 Multilevel Models; 6.3 A Multilevel AR(1) Model; 6.4 Application: Daily Alcohol Use; 6.5 Estimating This Model in SAS PROC MIXED; 6.6 Predicting the Individual AR(1) Coefficients; 6.7 Discussion; 7 The State-Space Approach to Modeling Dynamic Processes; 7.1 Gaussian State-Space Models; 7.2 Some Special Cases of State-Space Models; 7.3 Parameter Estimation
7.4 Application 1: Connectivity Analysis with fMRI Data; 7.5 Application 2: Testing the Induced Demand Hypothesis from Matched Traffic Profiles; 7.6 Conclusions; 8 The Control of Behavioral Input/Output Systems; 8.1 A Typical Input/Output System; 8.2 Modeling System Dynamics; 8.3 Controller Strategies to Meet an Output Target; 8.4 Fitting Dynamic Models to Intensive Longitudinal Data; 9 Dynamical Systems Modeling: An Application to the Regulation of Intimacy and Disclosure in Marriage; 9.1 Self-Regulation and Intrinsic Dynamics; 9.2 Coupled Regulation and Coupled Dynamics
9.3 Time-Delay Embedding; 9.4 Accounting for Individual Differences in Dynamics; 9.5 Application: Daily Intimacy and Disclosure in Married Couples; 9.6 Discussion; 10 Point Process Models for Event History Data: Applications in Behavioral Science; 10.1 Ecological Momentary Assessment of Smoking; 10.2 Point Process Models; 10.3 Application: An EMA Study of Smoking Data; 10.4 Discussion of Results; 10.5 Multivariate Point Patterns; 11 Emerging Technologies and Next-Generation Intensive Longitudinal Data Collection; 11.1 Intensive Data Collection Systems; 11.2 Statistical Issues for Intensive Longitudinal Measurement
Record Nr. UNINA-9910792235603321
Oxford ; ; New York, : Oxford University Press, 2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui