Missing data in clinical studies [[electronic resource] /] / Geert Molenberghs, Michael G. Kenward |
Autore | Molenberghs Geert |
Pubbl/distr/stampa | Chichester, Eng. ; ; Hoboken, NJ, : J. Wiley & Sons, c2007 |
Descrizione fisica | 1 online resource (528 p.) |
Disciplina | 610.724 |
Altri autori (Persone) | KenwardMichael G. <1956-> |
Collana | Statistics in practice |
Soggetto topico |
Clinical trials - Statistical methods
Missing observations (Statistics) |
Soggetto genere / forma | Electronic books. |
ISBN |
1-280-83950-3
9786610839506 0-470-51044-7 0-470-51043-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Missing Data in Clinical Studies; Contents; Preface; Acknowledgements; I Preliminaries; 1 Introduction; 1.1 From Imbalance to the Field of Missing Data Research; 1.2 Incomplete Data in Clinical Studies; 1.3 MAR, MNAR, and Sensitivity Analysis; 1.4 Outline of the Book; 2 Key Examples; 2.1 Introduction; 2.2 The Vorozole Study; 2.3 The Orthodontic Growth Data; 2.4 Mastitis in Dairy Cattle; 2.5 The Depression Trials; 2.6 The Fluvoxamine Trial; 2.7 The Toenail Data; 2.8 Age-Related Macular Degeneration Trial; 2.9 The Analgesic Trial; 2.10 The Slovenian Public Opinion Survey
3 Terminology and Framework3.1 Modelling Incompleteness; 3.2 Terminology; 3.3 Missing Data Frameworks; 3.4 Missing Data Mechanisms; 3.5 Ignorability; 3.6 Pattern-Mixture Models; Part II Classical Techniques and the Need for Modelling; 4 A Perspective on Simple Methods; 4.1 Introduction; 4.1.1 Measurement model; 4.1.2 Method for handling missingness; 4.2 Simple Methods; 4.2.1 Complete case analysis; 4.2.2 Imputation methods; 4.2.3 Last observation carried forward; 4.3 Problems with Complete Case Analysis and Last Observation Carried Forward 4.4 Using the Available Cases: a Frequentist versus a Likelihood Perspective4.4.1 A bivariate normal population; 4.4.2 An incomplete contingency table; 4.5 Intention to Treat; 4.6 Concluding Remarks; 5 Analysis of the Orthodontic Growth Data; 5.1 Introduction and Models; 5.2 The Original, Complete Data; 5.3 Direct Likelihood; 5.4 Comparison of Analyses; 5.5 Example SAS Code for Multivariate Linear Models; 5.6 Comparative Power under Different Covariance Structures; 5.7 Concluding Remarks; 6 Analysis of the Depression Trials; 6.1 View 1: Longitudinal Analysis 6.2 Views 2a and 2b and All versus Two Treatment ArmsIII Missing at Random and Ignorability; 7 The Direct Likelihood Method; 7.1 Introduction; 7.2 Ignorable Analyses in Practice; 7.3 The Linear Mixed Model; 7.4 Analysis of the Toenail Data; 7.5 The Generalized Linear Mixed Model; 7.6 The Depression Trials; 7.7 The Analgesic Trial; 8 The Expectation-Maximization Algorithm; 8.1 Introduction; 8.2 The Algorithm; 8.2.1 The initial step; 8.2.2 The E step; 8.2.3 The M step; 8.3 Missing Information; 8.4 Rate of Convergence; 8.5 EM Acceleration; 8.6 Calculation of Precision Estimates 8.7 A Simple Illustration8.8 Concluding Remarks; 9 Multiple Imputation; 9.1 Introduction; 9.2 The Basic Procedure; 9.3 Theoretical Justification; 9.4 Inference under Multiple Imputation; 9.5 Efficiency; 9.6 Making Proper Imputations; 9.7 Some Roles for Multiple Imputation; 9.8 Concluding Remarks; 10 Weighted Estimating Equations; 10.1 Introduction; 10.2 Inverse Probability Weighting; 10.3 Generalized Estimating Equations for Marginal Models; 10.3.1 Marginal models for non-normal data; 10.3.2 Generalized estimating equations; 10.3.3 A method based on linearization 10.4 Weighted Generalized Estimating Equations |
Record Nr. | UNINA-9910143744303321 |
Molenberghs Geert | ||
Chichester, Eng. ; ; Hoboken, NJ, : J. Wiley & Sons, c2007 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Missing data in clinical studies [[electronic resource] /] / Geert Molenberghs, Michael G. Kenward |
Autore | Molenberghs Geert |
Pubbl/distr/stampa | Chichester, Eng. ; ; Hoboken, NJ, : J. Wiley & Sons, c2007 |
Descrizione fisica | 1 online resource (528 p.) |
Disciplina | 610.724 |
Altri autori (Persone) | KenwardMichael G. <1956-> |
Collana | Statistics in practice |
Soggetto topico |
Clinical trials - Statistical methods
Missing observations (Statistics) |
ISBN |
1-280-83950-3
9786610839506 0-470-51044-7 0-470-51043-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Missing Data in Clinical Studies; Contents; Preface; Acknowledgements; I Preliminaries; 1 Introduction; 1.1 From Imbalance to the Field of Missing Data Research; 1.2 Incomplete Data in Clinical Studies; 1.3 MAR, MNAR, and Sensitivity Analysis; 1.4 Outline of the Book; 2 Key Examples; 2.1 Introduction; 2.2 The Vorozole Study; 2.3 The Orthodontic Growth Data; 2.4 Mastitis in Dairy Cattle; 2.5 The Depression Trials; 2.6 The Fluvoxamine Trial; 2.7 The Toenail Data; 2.8 Age-Related Macular Degeneration Trial; 2.9 The Analgesic Trial; 2.10 The Slovenian Public Opinion Survey
3 Terminology and Framework3.1 Modelling Incompleteness; 3.2 Terminology; 3.3 Missing Data Frameworks; 3.4 Missing Data Mechanisms; 3.5 Ignorability; 3.6 Pattern-Mixture Models; Part II Classical Techniques and the Need for Modelling; 4 A Perspective on Simple Methods; 4.1 Introduction; 4.1.1 Measurement model; 4.1.2 Method for handling missingness; 4.2 Simple Methods; 4.2.1 Complete case analysis; 4.2.2 Imputation methods; 4.2.3 Last observation carried forward; 4.3 Problems with Complete Case Analysis and Last Observation Carried Forward 4.4 Using the Available Cases: a Frequentist versus a Likelihood Perspective4.4.1 A bivariate normal population; 4.4.2 An incomplete contingency table; 4.5 Intention to Treat; 4.6 Concluding Remarks; 5 Analysis of the Orthodontic Growth Data; 5.1 Introduction and Models; 5.2 The Original, Complete Data; 5.3 Direct Likelihood; 5.4 Comparison of Analyses; 5.5 Example SAS Code for Multivariate Linear Models; 5.6 Comparative Power under Different Covariance Structures; 5.7 Concluding Remarks; 6 Analysis of the Depression Trials; 6.1 View 1: Longitudinal Analysis 6.2 Views 2a and 2b and All versus Two Treatment ArmsIII Missing at Random and Ignorability; 7 The Direct Likelihood Method; 7.1 Introduction; 7.2 Ignorable Analyses in Practice; 7.3 The Linear Mixed Model; 7.4 Analysis of the Toenail Data; 7.5 The Generalized Linear Mixed Model; 7.6 The Depression Trials; 7.7 The Analgesic Trial; 8 The Expectation-Maximization Algorithm; 8.1 Introduction; 8.2 The Algorithm; 8.2.1 The initial step; 8.2.2 The E step; 8.2.3 The M step; 8.3 Missing Information; 8.4 Rate of Convergence; 8.5 EM Acceleration; 8.6 Calculation of Precision Estimates 8.7 A Simple Illustration8.8 Concluding Remarks; 9 Multiple Imputation; 9.1 Introduction; 9.2 The Basic Procedure; 9.3 Theoretical Justification; 9.4 Inference under Multiple Imputation; 9.5 Efficiency; 9.6 Making Proper Imputations; 9.7 Some Roles for Multiple Imputation; 9.8 Concluding Remarks; 10 Weighted Estimating Equations; 10.1 Introduction; 10.2 Inverse Probability Weighting; 10.3 Generalized Estimating Equations for Marginal Models; 10.3.1 Marginal models for non-normal data; 10.3.2 Generalized estimating equations; 10.3.3 A method based on linearization 10.4 Weighted Generalized Estimating Equations |
Record Nr. | UNINA-9910830651403321 |
Molenberghs Geert | ||
Chichester, Eng. ; ; Hoboken, NJ, : J. Wiley & Sons, c2007 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Missing data in clinical studies / / Geert Molenberghs, Michael G. Kenward |
Autore | Molenberghs Geert |
Pubbl/distr/stampa | Chichester, Eng. ; ; Hoboken, NJ, : J. Wiley & Sons, c2007 |
Descrizione fisica | 1 online resource (528 p.) |
Disciplina | 610.724 |
Altri autori (Persone) | KenwardMichael G. <1956-> |
Collana | Statistics in practice |
Soggetto topico |
Clinical trials - Statistical methods
Missing observations (Statistics) |
ISBN |
1-280-83950-3
9786610839506 0-470-51044-7 0-470-51043-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Missing Data in Clinical Studies; Contents; Preface; Acknowledgements; I Preliminaries; 1 Introduction; 1.1 From Imbalance to the Field of Missing Data Research; 1.2 Incomplete Data in Clinical Studies; 1.3 MAR, MNAR, and Sensitivity Analysis; 1.4 Outline of the Book; 2 Key Examples; 2.1 Introduction; 2.2 The Vorozole Study; 2.3 The Orthodontic Growth Data; 2.4 Mastitis in Dairy Cattle; 2.5 The Depression Trials; 2.6 The Fluvoxamine Trial; 2.7 The Toenail Data; 2.8 Age-Related Macular Degeneration Trial; 2.9 The Analgesic Trial; 2.10 The Slovenian Public Opinion Survey
3 Terminology and Framework3.1 Modelling Incompleteness; 3.2 Terminology; 3.3 Missing Data Frameworks; 3.4 Missing Data Mechanisms; 3.5 Ignorability; 3.6 Pattern-Mixture Models; Part II Classical Techniques and the Need for Modelling; 4 A Perspective on Simple Methods; 4.1 Introduction; 4.1.1 Measurement model; 4.1.2 Method for handling missingness; 4.2 Simple Methods; 4.2.1 Complete case analysis; 4.2.2 Imputation methods; 4.2.3 Last observation carried forward; 4.3 Problems with Complete Case Analysis and Last Observation Carried Forward 4.4 Using the Available Cases: a Frequentist versus a Likelihood Perspective4.4.1 A bivariate normal population; 4.4.2 An incomplete contingency table; 4.5 Intention to Treat; 4.6 Concluding Remarks; 5 Analysis of the Orthodontic Growth Data; 5.1 Introduction and Models; 5.2 The Original, Complete Data; 5.3 Direct Likelihood; 5.4 Comparison of Analyses; 5.5 Example SAS Code for Multivariate Linear Models; 5.6 Comparative Power under Different Covariance Structures; 5.7 Concluding Remarks; 6 Analysis of the Depression Trials; 6.1 View 1: Longitudinal Analysis 6.2 Views 2a and 2b and All versus Two Treatment ArmsIII Missing at Random and Ignorability; 7 The Direct Likelihood Method; 7.1 Introduction; 7.2 Ignorable Analyses in Practice; 7.3 The Linear Mixed Model; 7.4 Analysis of the Toenail Data; 7.5 The Generalized Linear Mixed Model; 7.6 The Depression Trials; 7.7 The Analgesic Trial; 8 The Expectation-Maximization Algorithm; 8.1 Introduction; 8.2 The Algorithm; 8.2.1 The initial step; 8.2.2 The E step; 8.2.3 The M step; 8.3 Missing Information; 8.4 Rate of Convergence; 8.5 EM Acceleration; 8.6 Calculation of Precision Estimates 8.7 A Simple Illustration8.8 Concluding Remarks; 9 Multiple Imputation; 9.1 Introduction; 9.2 The Basic Procedure; 9.3 Theoretical Justification; 9.4 Inference under Multiple Imputation; 9.5 Efficiency; 9.6 Making Proper Imputations; 9.7 Some Roles for Multiple Imputation; 9.8 Concluding Remarks; 10 Weighted Estimating Equations; 10.1 Introduction; 10.2 Inverse Probability Weighting; 10.3 Generalized Estimating Equations for Marginal Models; 10.3.1 Marginal models for non-normal data; 10.3.2 Generalized estimating equations; 10.3.3 A method based on linearization 10.4 Weighted Generalized Estimating Equations |
Record Nr. | UNINA-9910877328503321 |
Molenberghs Geert | ||
Chichester, Eng. ; ; Hoboken, NJ, : J. Wiley & Sons, c2007 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Multiple imputation and its application [[electronic resource] /] / James R. Carpenter and Michael G. Kenward |
Autore | Carpenter James R |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Chichester, West Sussex, U.K., : Wiley, 2013 |
Descrizione fisica | 1 online resource (490 pages) : illustrations, tables |
Disciplina | 610.724 |
Altri autori (Persone) | KenwardMichael G. <1956-> |
Collana |
Statistics in Practice
Statistics in practice |
Soggetto topico |
Statistics
Multiple imputation (Statistics) Medicine - Research - Statistical methods |
ISBN |
1-119-94228-4
1-119-94227-6 1-118-44261-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Machine generated contents note: Reasons for missing data Summary -- The Multiple Imputation Procedure and Its Justification -- Multiple imputation of binary and ordinal data -- Imputation of unordered categorical data -- Non-linear relationships -- Interactions -- Survival data, skips and large datasets -- Multilevel multiple imputation -- Sensitivity analysis: MI unleashed -- Including survey weights -- Robust Multiple Imputation. |
Record Nr. | UNINA-9910141616403321 |
Carpenter James R | ||
Chichester, West Sussex, U.K., : Wiley, 2013 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Multiple imputation and its application / / James R. Carpenter and Michael G. Kenward |
Autore | Carpenter James R |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Chichester, West Sussex, U.K., : Wiley, 2013 |
Descrizione fisica | 1 online resource (490 pages) : illustrations, tables |
Disciplina | 610.72/4 |
Altri autori (Persone) | KenwardMichael G. <1956-> |
Collana | Statistics in practice |
Soggetto topico |
Statistics
Multiple imputation (Statistics) Medicine - Research - Statistical methods |
ISBN |
1-119-94228-4
1-119-94227-6 1-118-44261-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Machine generated contents note: Reasons for missing data Summary -- The Multiple Imputation Procedure and Its Justification -- Multiple imputation of binary and ordinal data -- Imputation of unordered categorical data -- Non-linear relationships -- Interactions -- Survival data, skips and large datasets -- Multilevel multiple imputation -- Sensitivity analysis: MI unleashed -- Including survey weights -- Robust Multiple Imputation. |
Record Nr. | UNINA-9910819826003321 |
Carpenter James R | ||
Chichester, West Sussex, U.K., : Wiley, 2013 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|