{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":18,"n_cols":5,"rows_kept":18,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[10,2,10,3],[11,2,11,3],[12,2,12,3],[15,2,15,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910155108403321"]
[null,null,"Autore",null,"Mallinckrodt Craig H. <1958, >"]
[null,null,"Titolo",null,"Analyzing longitudinal clinical trial data : a practical guide / / by Craig Mallinckrodt and Ilya Lipkovich"]
[null,null,"Pubbl/distr/stampa",null,"Boca Raton, FL : , : Chapman and Hall/CRC, an imprint of Taylor and Francis, , 2016"]
[null,null,"ISBN",null,"1-351-73768-6"]
[{"$nulls":4},"1-315-18663-2"]
[{"$nulls":4},"1-351-73769-4"]
[null,null,"Descrizione fisica",null,"1 online resource (330 pages) : illustrations, tables"]
[null,null,"Collana",null,"Chapman & Hall/CRC Biostatistics Series"]
[null,null,"Disciplina",null,"615.5072/4"]
[null,null,"Soggetti",null,"Clinical trials"]
[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,"Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgments -- List of Tables -- List of Figures -- List of Code Fragments -- Section I: Background and Setting -- 1: Introduction -- 2: Objectives and Estimands�Determining What to Estimate -- 3: Study Design�Collecting the Intended Data -- 4: Example Data -- 5: Mixed-Effects Models Review -- Section II: Modeling the Observed Data -- 6: Choice of Dependent Variable and Statistical Test -- 7: Modeling Covariance (Correlation) -- 8: Modeling Means Over Time -- 9: Accounting for Covariates -- 10: Categorical Data -- 11: Model Checking and Verification -- Section III: Methods for Dealing with Missing Data -- 12: Overview of Missing Data -- 13: Simple and Ad Hoc Approaches for Dealing with Missing Data -- 14: Direct Maximum Likelihood -- 15: Multiple Imputation -- 16: Inverse Probability Weighted Generalized Estimated Equations -- 17: Doubly Robust Methods -- 18: MNAR Methods -- 19: Methods for Incomplete Categorical Data -- Section IV: A Comprehensive Approach to Study Development and Analyses -- 20: Developing Statistical Analysis Plans -- 21: Example Analyses of Clinical Trial Data -- References -- Index."]
[null,null,null,"Sommario/riassunto","Analyzing Longitudinal Clinical Trial Data: A Practical Guide provides practical and easy to implement approaches for bringing the latest theory on analysis of longitudinal clinical trial data into routine practice. The book, with its example-oriented approach that includes numerous SAS and R code fragments, is an essential resource for statisticians and graduate students specializing in medical research. "]
[{"$nulls":4},"The authors provide clear descriptions of the relevant statistical theory and illustrate practical considerations for modeling longitudinal data. Topics covered include choice of endpoint and statistical test; modeling means and the correlations between repeated measurements; accounting for covariates; modeling categorical data; model verification; methods for incomplete (missing) data that includes the latest developments in sensitivity analyses, along with approaches for and issues in choosing estimands; and means for preventing missing data. Each chapter stands alone in its coverage of a topic. The concluding chapters provide detailed advice on how to integrate these independent topics into an over-arching study development process and statistical analysis plan."]