05546nam 2200709Ia 450 991014126190332120230801223249.01-280-76813-497866136789041-118-27971-91-118-27972-71-118-27969-7(CKB)2670000000205432(EBL)836592(OCoLC)796796332(SSID)ssj0000677229(PQKBManifestationID)11446001(PQKBTitleCode)TC0000677229(PQKBWorkID)10693278(PQKB)10440920(MiAaPQ)EBC836592(Au-PeEL)EBL836592(CaPaEBR)ebr10570760(CaONFJC)MIL367890(EXLCZ)99267000000020543220111119d2012 uy 0engur|n|---|||||txtccrDesign and analysis of experiments in the health sciences[electronic resource] /Gerald van Belle, Kathleen F. Kerr1st ed.Hoboken, N.J. Wiley20121 online resource (247 p.)Description based upon print version of record.0-470-12727-9 Includes bibliographical references and index.Design and Analysis of Experiments in the Health Sciences; Contents; Preface; 1 The Basics; 1.1 Four Basic Questions; 1.2 Variation; 1.3 Principles of Design and Analysis; 1.4 Experiments and Observational Studies; 1.5 Illustrative Applications of Principles; 1.6 Experiments in the Health Sciences; 1.7 Adaptive Allocation; 1.7.1 Equidistribution; 1.7.2 Adaptive Allocation Techniques; 1.8 Sample Size Calculations; 1.9 Statistical Models for the Data; 1.10 Analysis and Presentation; 1.10.1 Graph the Data in Several Ways; 1.10.2 Assess Assumptions of the Statistical Model1.10.3 Confirmatory and Exploratory Analysis1.10.4 Missing Data Need Careful Accounting; 1.10.5 Statistical Software; 1.11 Notes; 1.11.1 Characterization Studies; 1.11.2 Additional Comments on Balance; 1.11.3 Linear and Nonlinear Models; 1.11.4 Analysis of Variance Versus Regression Analysis; 1.12 Summary; 1.13 Problems; 2 Completely Randomized Designs; 2.1 Randomization; 2.2 Hypotheses and Sample Size; 2.3 Estimation and Analysis; 2.4 Example; 2.5 Discussion and Extensions; 2.5.1 Preparing Data for Computer Analysis; 2.5.2 Treatment Assignment in this Example; 2.5.3 Check on Randomization2.5.4 Partitioning the Treatment Sum of Squares2.5.5 Alternative Endpoints; 2.5.6 Dummy Variables; 2.5.7 Contrasts; 2.6 Randomization; 2.7 Hypotheses and Sample Size; 2.8 Estimation and Analysis; 2.9 Example; 2.10 Discussion and Extensions; 2.10.1 Two Roles for ANCOVA; 2.10.2 Partitioning of Sums of Squares; 2.10.3 Assumption of Parallelism; 2.11 Notes; 2.11.1 Constrained Randomization; 2.11.2 Assumptions of the Analysis of Variance and Covariance; 2.11.3 When the Assumptions Don't Hold; 2.11.4 Alternative Graphical Displays; 2.11.5 Sample Sizes for More Than Two Levels2.11.6 Limitations of Computer Output2.11.7 Unequal Sample Sizes; 2.11.8 Design Implications of the CRD; 2.11.9 Power and Alternative Hypotheses; 2.11.10 Regression or Analysis of Variance?; 2.11.11 Bioassay; 2.12 Summary; 2.13 Problems; 3 Randomized Block Designs; 3.1 Randomization; 3.2 Hypotheses and Sample Size; 3.3 Estimation and Analysis; 3.4 Example; 3.5 Discussion and Extensions; 3.5.1 Evaluating Model Assumptions; 3.5.2 Multiple Comparisons; 3.5.3 Number of Treatments and Block Size; 3.5.4 Missing Data; 3.5.5 Does It Always Pay to Block?; 3.5.6 Concomitant Variables; 3.5.7 Imbalance3.6 Randomization3.7 Hypotheses and Sample Size; 3.8 Estimation and Analysis; 3.9 Example; 3.10 Discussion and Extensions; 3.10.1 Implications of the Model; 3.10.2 Number of Latin Squares; 3.11 Randomization; 3.12 Hypotheses and Sample Size; 3.13 Estimation and Analysis; 3.14 Example; 3.15 Discussion and Extensions; 3.15.1 Partially Balanced Incomplete Block Designs; 3.16 Notes; 3.16.1 Analysis Follows Design; 3.16.2 Relative Efficiency; 3.16.3 Additivity of the Model; 3.17 Summary; 3.18 Problems; 4 Factorial Designs; 4.1 Randomization; 4.2 Hypotheses and Sample Size4.3 Estimation and Analysis An accessible and practical approach to the design and analysis of experiments in the health sciences Design and Analysis of Experiments in the Health Sciences provides a balanced presentation of design and analysis issues relating to data in the health sciences and emphasizes new research areas, the crucial topic of clinical trials, and state-of-the- art applications. Advancing the idea that design drives analysis and analysis reveals the design, the book clearly explains how to apply design and analysis principles in animal, human, and laboratory experiments whilExperimental designMedical informaticsMedical sciencesStatistical methodsExperimental design.Medical informatics.Medical sciencesStatistical methods.610.72/7MAT029000bisacshVan Belle Gerald266785Kerr Kathleen F.1970-951145MiAaPQMiAaPQMiAaPQBOOK9910141261903321Design and analysis of experiments in the health sciences2150195UNINA