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Missing Data [[electronic resource] ] : A Gentle Introduction
| Missing Data [[electronic resource] ] : A Gentle Introduction |
| Autore | McKnight Patrick E |
| Pubbl/distr/stampa | New York, : Guilford Press, 2007 |
| Descrizione fisica | 1 online resource (268 p.) |
| Disciplina | 300.72 |
| Collana | Methodology in the Social Sciences |
| Soggetto topico |
Missing observations (Statistics)
Social sciences |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-86915-5
9786611869151 1-60623-221-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Matter; Chapter 1; Chapter 2; Chapter 3; Chapter 4; Chapter 5; Chapter 6; Chapter 7; Chapter 8; Chapter 9; Chapter 10; Chapter 11; Chapter 12; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910454092103321 |
McKnight Patrick E
|
||
| New York, : Guilford Press, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Missing Data [[electronic resource] ] : A Gentle Introduction
| Missing Data [[electronic resource] ] : A Gentle Introduction |
| Autore | McKnight Patrick E |
| Pubbl/distr/stampa | New York, : Guilford Press, 2007 |
| Descrizione fisica | 1 online resource (268 p.) |
| Disciplina | 300.72 |
| Collana | Methodology in the Social Sciences |
| Soggetto topico |
Missing observations (Statistics)
Social sciences |
| ISBN |
1-281-86915-5
9786611869151 1-60623-221-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Matter; Chapter 1; Chapter 2; Chapter 3; Chapter 4; Chapter 5; Chapter 6; Chapter 7; Chapter 8; Chapter 9; Chapter 10; Chapter 11; Chapter 12; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910782793703321 |
|
McKnight Patrick E
|
||
| New York, : Guilford Press, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Missing Data [[electronic resource] ] : A Gentle Introduction
| Missing Data [[electronic resource] ] : A Gentle Introduction |
| Autore | McKnight Patrick E |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York, : Guilford Press, 2007 |
| Descrizione fisica | 1 online resource (268 p.) |
| Disciplina | 300.72 |
| Collana | Methodology in the Social Sciences |
| Soggetto topico |
Missing observations (Statistics)
Social sciences |
| ISBN |
1-281-86915-5
9786611869151 1-60623-221-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Matter; Chapter 1; Chapter 2; Chapter 3; Chapter 4; Chapter 5; Chapter 6; Chapter 7; Chapter 8; Chapter 9; Chapter 10; Chapter 11; Chapter 12; References; Author Index; Subject Index |
| Record Nr. | UNINA-9910824213403321 |
|
McKnight Patrick E
|
||
| New York, : Guilford Press, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Missing data in clinical studies [[electronic resource] /] / Geert Molenberghs, Michael G. Kenward
| 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
| 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 [[electronic resource] /] / Geert Molenberghs, Michael G. Kenward
| 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-9910841022103321 |
|
Molenberghs Geert
|
||
| Chichester, Eng. ; ; Hoboken, NJ, : J. Wiley & Sons, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Missing data methods [[electronic resource] ] : cross-sectional methods and applications / / edited by David M. Drukker
| Missing data methods [[electronic resource] ] : cross-sectional methods and applications / / edited by David M. Drukker |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bingley [England], : Emerald Group Pub., 2011 |
| Descrizione fisica | 1 online resource (352 p.) |
| Disciplina | 330.015195 |
| Altri autori (Persone) | DrukkerDavid M |
| Collana | Advances in econometrics |
| Soggetto topico | Missing observations (Statistics) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-35486-1
9786613354860 1-78052-525-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Missing Data Methods: Cross-sectional Methods and Applications; Copyright Page; Contents; List of contributors; Introduction; Cross-sectional methods and applications; Acknowledgments; References; The elephant in the corner: a cautionary tale about measurement error in treatment effects models; Introduction; Consequences of measurement error; Evidence of measurement error; Causal inference under conditional independence; Estimation in the Absence of Measurement Error; Monte carlo study; Results; Conclusion; Notes; Acknowledgments; References
Recent developments in semiparametric and nonparametric estimation of panel data models with incomplete information: A selected reviewIntroduction; Models with incomplete data; Measurement Error; Concluding remarks; Notes; References; Likelihood-based estimators for endogenous or truncated samples in standard stratified sampling; Introduction; Four types of estimators; A simulation study; Conclusions; ACKNOWLEDGMENTS; References; Taking into Account FX-FX for Asymptotic Variance; Efficient estimation of the dose-response function under ignorability using subclassification on the covariates IntroductionModel, identification, and estimator; Large sample results; Simulations; Extensions and final remarks; Notes; Acknowledgments; References; Average derivative estimation with missing responses; Introduction; The model and estimator; Asymptotic results; Monte carlo experiments; Acknowledgments; References; Auxiliary Notation and Results; Main Proofs; Consistent estimation and orthogonality; Introduction; Preliminaries and notation; The likelihood function: three orthogonality concepts; Inference based on the score; Inconsistency of the integrated likelihood estimator; Conclusion NotesAcknowledgment; References; Orthogonality in the single index model; On the estimation of selection models when participation is endogenous and misclassified; Introduction; The model and estimator; Sampling algorithm; Simulated data example; Summary and conclusions; Notes; Acknowledgments; References; summary tables for additional simulations; Process for simulating non--normal errors; Efficient probit estimation with partially missing covariates; Introduction; Model Specification; Efficient estimators and variances; Testing assumptions and possible modifications; Other models SimulationsEmpirical application to portfolio allocation; Conclusion; Notes; Acknowledgment; References; Efficient estimators of Bx and Bw; Variances of Bx and Bw; The case of observed Y; Nonlinear difference-in-difference treatment effect estimation: A distributional analysis; Introduction; Methodology; Monte Carlo simulation; Empirical application; Conclusion; Notes; Acknowledgment; References; Bayesian analysis of multivariate sample selection models using gaussian copulas; Introduction; Copulas; Model; Estimation; Applications; Concluding remarks; Acknowledgments; References Estimating the average treatment effect based on direct estimation of the conditional treatment effect |
| Record Nr. | UNINA-9910457762403321 |
| Bingley [England], : Emerald Group Pub., 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Missing data methods [[electronic resource] ] : cross-sectional methods and applications / / edited by David M. Drukker
| Missing data methods [[electronic resource] ] : cross-sectional methods and applications / / edited by David M. Drukker |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bingley [England], : Emerald Group Pub., 2011 |
| Descrizione fisica | 1 online resource (352 p.) |
| Disciplina | 330.015195 |
| Altri autori (Persone) | DrukkerDavid M |
| Collana | Advances in econometrics |
| Soggetto topico |
Business & Economics - Econometrics
Economics Econometrics Missing observations (Statistics) Economics - Statistical methods |
| ISBN |
1-283-35486-1
9786613354860 1-78052-525-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction / David M. Drukker -- The elephant in the corner : a cautionary tale about measurement error in treatment effects models / Daniel L. Millimet -- Recent developments in semiparametric and nonparametric estimation of panel data models with incomplete information : a selected review / Yu Yvette Zhang, Qi Li, Dong Li -- Likelihood-based estimators for endogenous or truncated samples in standard stratified sampling / Myoung-jae Lee, Sanghyeok Lee -- Efficient estimation of the dose-response function under ignorability using subclassification on the covariates / Matias D. Cattaneo, Max H. Farrell -- Average derivative estimation with missing responses / Francesco Bravo, Kim P. Huynh, David T. Jacho-Chávez -- Consistent estimation and orthogonality / Tiemen Woutersen -- On the estimation of selection models when participation is endogenous and misclassified / Ian M. McCarthy, Rusty Tchernis -- Efficient probit estimation with partially missing covariates / Denis Conniffe, Donal O'Neill -- Nonlinear difference-in-difference treatment effect estimation : a distributional analysis / Kim P. Huynh, David T. Jacho-Chávez, Marcel C. Voia -- Bayesian analysis of multivariate sample selection models using Gaussian copulas / Phillip Li, Mohammad Arshad Rahman -- Estimating the average treatment effect based on direct estimation of the conditional treatment effect / Jingping Gu, Juan Lin, Dandan Liu -- A missing variable imputation methodology with an empirical application / Gayaneh Kyureghian, Oral Capps, Rodolfo M. Nayga. |
| Record Nr. | UNINA-9910781940403321 |
| Bingley [England], : Emerald Group Pub., 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Missing data methods [[electronic resource] ] : cross-sectional methods and applications / / edited by David M. Drukker
| Missing data methods [[electronic resource] ] : cross-sectional methods and applications / / edited by David M. Drukker |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bingley [England], : Emerald Group Pub., 2011 |
| Descrizione fisica | 1 online resource (352 p.) |
| Disciplina | 330.015195 |
| Altri autori (Persone) | DrukkerDavid M |
| Collana | Advances in econometrics |
| Soggetto topico |
Business & Economics - Econometrics
Economics Econometrics Missing observations (Statistics) Economics - Statistical methods |
| ISBN |
1-283-35486-1
9786613354860 1-78052-525-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction / David M. Drukker -- The elephant in the corner : a cautionary tale about measurement error in treatment effects models / Daniel L. Millimet -- Recent developments in semiparametric and nonparametric estimation of panel data models with incomplete information : a selected review / Yu Yvette Zhang, Qi Li, Dong Li -- Likelihood-based estimators for endogenous or truncated samples in standard stratified sampling / Myoung-jae Lee, Sanghyeok Lee -- Efficient estimation of the dose-response function under ignorability using subclassification on the covariates / Matias D. Cattaneo, Max H. Farrell -- Average derivative estimation with missing responses / Francesco Bravo, Kim P. Huynh, David T. Jacho-Chávez -- Consistent estimation and orthogonality / Tiemen Woutersen -- On the estimation of selection models when participation is endogenous and misclassified / Ian M. McCarthy, Rusty Tchernis -- Efficient probit estimation with partially missing covariates / Denis Conniffe, Donal O'Neill -- Nonlinear difference-in-difference treatment effect estimation : a distributional analysis / Kim P. Huynh, David T. Jacho-Chávez, Marcel C. Voia -- Bayesian analysis of multivariate sample selection models using Gaussian copulas / Phillip Li, Mohammad Arshad Rahman -- Estimating the average treatment effect based on direct estimation of the conditional treatment effect / Jingping Gu, Juan Lin, Dandan Liu -- A missing variable imputation methodology with an empirical application / Gayaneh Kyureghian, Oral Capps, Rodolfo M. Nayga. |
| Record Nr. | UNINA-9910806246103321 |
| Bingley [England], : Emerald Group Pub., 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The prevention and treatment of missing data in clinical trials [[electronic resource] /] / Panel on Handling Missing Data in Clinical Trials, Committee on National Statistics, Division of Behavioral and Social Sciences and Education
| The prevention and treatment of missing data in clinical trials [[electronic resource] /] / Panel on Handling Missing Data in Clinical Trials, Committee on National Statistics, Division of Behavioral and Social Sciences and Education |
| Pubbl/distr/stampa | Washington, D.C., : National Academies Press, 2010 |
| Descrizione fisica | 1 online resource (162 p.) |
| Disciplina | 615.50724 |
| Soggetto topico |
Missing observations (Statistics)
Clinical trials |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-282-97597-8
9786612975974 0-309-15815-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ""Front Matter""; ""Acknowledgments""; ""Contents""; ""Glossary""; ""Summary""; ""1 Introduction and Background""; ""2 Trial Designs to Reduce the Frequency of Missing Data""; ""3 Trial Strategies to Reduce the Frequency of Missing Data""; ""4 Drawing Inferences from Incomplete Data""; ""5 Principles and Methods of Sensitivity Analyses""; ""6 Conclusions and Recommendations""; ""References""; ""Appendix A: Clinical Trials: Overview and Terminology""; ""Appendix B: Biographical Sketches of Panel Members and Staff""; ""Committee on National Statistics"" |
| Record Nr. | UNINA-9910457123503321 |
| Washington, D.C., : National Academies Press, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
