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[null,"1.","Record Nr.",null,"UNINA9910143744303321"]
[null,null,"Autore",null,"Molenberghs Geert"]
[null,null,"Titolo",null,"Missing data in clinical studies [[electronic resource] /] / Geert Molenberghs, Michael G. Kenward"]
[null,null,"Pubbl/distr/stampa",null,"Chichester, Eng. ; ; Hoboken, NJ, : J. Wiley & Sons, c2007"]
[null,null,"ISBN",null,"1-280-83950-3"]
[{"$nulls":4},"9786610839506"]
[{"$nulls":4},"0-470-51044-7"]
[{"$nulls":4},"0-470-51043-9"]
[null,null,"Descrizione fisica",null,"1 online resource (528 p.)"]
[null,null,"Collana",null,"Statistics in practice"]
[null,null,"Disciplina",null,"610.724"]
[null,null,"Soggetti",null,"Clinical trials - Statistical methods"]
[{"$nulls":4},"Missing observations (Statistics)"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. 483-496) and index."]
[null,null,"Nota di contenuto",null,"Missing Data in Clinical Studies; Contents; Preface; Acknowledgements; I Preliminaries; 1 Introduction; 1.1 From Imbalance to the Field of Missing Data Research; 1.2 Incomplete Data in Clinical Studies; 1.3 MAR, MNAR, and Sensitivity Analysis; 1.4 Outline of the Book; 2 Key Examples; 2.1 Introduction; 2.2 The Vorozole Study; 2.3 The Orthodontic Growth Data; 2.4 Mastitis in Dairy Cattle; 2.5 The Depression Trials; 2.6 The Fluvoxamine Trial; 2.7 The Toenail Data; 2.8 Age-Related Macular Degeneration Trial; 2.9 The Analgesic Trial; 2.10 The Slovenian Public Opinion Survey"]
[{"$nulls":4},"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"]
[{"$nulls":4},"4.4 Using the Available Cases: a Frequentist versus a Likelihood Perspective4.4.1 A bivariate normal population; 4.4.2 An incomplete contingency table; 4.5 Intention to Treat; 4.6 Concluding Remarks; 5 "]
[{"$nulls":4},"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"]
[{"$nulls":4},"6.2 Views 2a and 2b and All versus Two Treatment ArmsIII Missing at Random and Ignorability; 7 The Direct Likelihood Method; 7.1 Introduction; 7.2 Ignorable Analyses in Practice; 7.3 The Linear Mixed Model; 7.4 Analysis of the Toenail Data; 7.5 The Generalized Linear Mixed Model; 7.6 The Depression Trials; 7.7 The Analgesic Trial; 8 The Expectation-Maximization Algorithm; 8.1 Introduction; 8.2 The Algorithm; 8.2.1 The initial step; 8.2.2 The E step; 8.2.3 The M step; 8.3 Missing Information; 8.4 Rate of Convergence; 8.5 EM Acceleration; 8.6 Calculation of Precision Estimates"]
[{"$nulls":4},"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"]
[{"$nulls":4},"10.4 Weighted Generalized Estimating Equations"]
[null,null,null,"Sommario/riassunto","Missing Data in Clinical Studies provides a comprehensive account of the problems arising when data from clinical and related studies are incomplete, and presents the reader with approaches to effectively address them. The text provides a critique of conventional and simple methods before moving on to discuss more advanced approaches. The authors focus on practical and modeling concepts, providing an extensive set of case studies to illustrate the problems described. Provides a practical guide to the analysis of clinical trials and related studies with missing data.Examines"]
[null,"2.","Record Nr.",null,"UNINA9910799485803321"]
[null,null,"Titolo",null,"Approximation and Online Algorithms : 21st International Workshop, WAOA 2023, Amsterdam, The Netherlands, September 7–8, 2023, Proceedings / / edited by Jarosław Byrka, Andreas Wiese"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"3-031-49815-1"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XII, 236 p. 35 illus., 13 illus. in color.)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science, , 1611-3349 ; ; 14297"]
[null,null,"Disciplina",null,"518.1"]
[null,null,"Soggetti",null,"Mathematics - Data processing"]
[{"$nulls":4},"Data structures (Computer science)"]
[{"$nulls":4},"Information theory"]
[{"$nulls":4},"Computer science - Mathematics"]
[{"$nulls":4},"Discrete mathematics"]
[{"$nulls":4},"Numerical analysis"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Computational Mathematics and Numerical Analysis"]
[{"$nulls":4},"Data Structures and Information Theory"]
[{"$nulls":4},"Discrete Mathematics in Computer Science"]
[{"$nulls":4},"Symbolic and Algebraic Manipulation"]
[{"$nulls":4},"Numerical Analysis"]
[{"$nulls":4},"Design and Analysis of Algorithms"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Optimization under Explorable Uncertainty: Adversarial and Stochastic Models -- Approximation Ineffectiveness of a Tour-Untangling Heuristic -- A Frequency-Competitive Query Strategy for Maintaining Low Collision Potential Among Moving Entities -- Approximating Maximum Edge 2-Coloring by Normalizing Graphs -- An Improved Deterministic Algorithm for the Online Min-Sum Set Cover Problem -- Greedy Minimum-Energy Scheduling -- Scheduling with Speed Predictions -- The Power of Amortization on Scheduling with Explorable Uncertainty -- Total Completion Time Scheduling Under Scenarios -- Approximating Fair k-Min-Sum-Radii in Euclidean Space -- Online hitting set of d-dimensional fat objects -- Approximation Schemes under Resource Augmentation for Knapsack and Packing "]
[{"$nulls":4},"Problems of Hyperspheres and Other Shapes -- Hitting Sets when the Shallow Cell Complexity is Small -- Any-Order Online Interval Selection -- Improved Approximations for Relative Survivable Network Design -- Independent set in k-Claw-Free Graphs: Conditional χ-boundedness and the Power of LP/SDP Relaxations -- Fast Parallel Algorithms for Submodular p-Superseparable Maximization."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 21st International Workshop on Approximation and Online Algorithms, WAOA 2023, held in Amsterdam, The Netherlands, during September 7–8, 2023 The 16 full papers included in this book are carefully reviewed and selected from 43 submissions. The topics of WAOA 2023 were algorithmic game theory, algorithmic trading, coloring and partitioning, competitive analysis, computational advertising, computational finance, cuts and connectivity, FPT-approximation algorithms, geometric problems, graph algorithms, inapproximability results, mechanism design, network design, packing and covering, paradigms for the design and analysis of approximation and online algorithms, resource augmentation, and scheduling problems."]