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OverviewAn introduction to state-of-the-art experimental designapproaches to better understand and interpret repeated measurementdata in cross-over designs. Repeated Measurements and Cross-Over Designs Features the close tie between the design, analysis, andpresentation of results Presents principles and rules that apply very generally to mostareas of research, such as clinical trials, agriculturalinvestigations, industrial procedures, quality control procedures, and epidemiological studies Includes many practical examples, such as PK/PD studies in thepharmaceutical industry, k-sample and one sample repeatedmeasurement designs for psychological studies, and residualeffects of different treatments in controlling conditions such asasthma, blood pressure, and diabetes. Utilizes SAS(R) software to draw necessary inferences. All SAS output and data sets are available via the book's relatedwebsite. This book is ideal for a broad audience including statisticiansin pre-clinical research, researchers in psychology, sociology, politics, marketing, and engineering. Full Product DetailsAuthor: Damaraju Raghavarao , Lakshmi PadgettPublisher: John Wiley & Sons Inc Imprint: John Wiley & Sons Inc ISBN: 9781118709122ISBN 10: 1118709128 Pages: 272 Publication Date: 18 March 2014 Audience: Professional and scholarly , Professional & Vocational Format: Electronic book text Publisher's Status: Active Availability: Available To Order ![]() We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsPreface xi 1. Introduction 1 1.1 Introduction 1 1.2 One-Sample RMD 2 1.3 k-Sample RMD 4 1.4 Split-Plot Designs 7 1.5 Growth Curves 13 1.6 Cross-Over Designs 14 1.7 Two-Period Cross-Over Designs 18 1.8 Modifications in Cross-Over Designs 19 1.9 Nonparametric Methods 22 References 23 2. One-Sample Repeated Measurement Designs 25 2.1 Introduction 25 2.2 Testing for Sphericity Condition 26 2.3 Univariate ANOVA for One-Sample RMD 29 2.4 Multivariate Methods for One-Sample RMD 32 2.5 Univariate ANOVA Under Nonsphericity Condition 34 2.6 Numerical Example 35 2.7 Concordance Correlation Coefficient 41 2.8 Multiresponse Concordance Correlation Coefficient 44 2.9 Repeated Measurements with Binary Response 47 References 51 3. k-Sample Repeated Measurements Design 53 3.1 Introduction 53 3.2 Test for the Equality of Dispersion Matrices and SphericityCondition of k-Dispersion Matrices 54 3.3 Univariate ANOVA for k-Sample RMD 57 3.4 Multivariate Methods for k-Sample RMD 60 3.5 Numerical Example 63 3.6 Multivariate Methods with Unequal Dispersion Matrices 67 3.7 Analysis with Ordered Categorical Response 72 References 75 4. Growth Curve Models 77 4.1 Introduction 77 4.2 Sigmoidal Curves 78 4.3 Analysis of Mixed Models 84 4.4 Simple Linear Growth Curve Model 90 4.5 Nonlinear Growth Curve Model 92 4.6 Numerical Example 93 4.7 Joint Action Models 100 References 103 5. Cross-Over Designs without Residual Effects 105 5.1 Introduction 105 5.2 Fixed Effects Analysis of CODWOR 107 5.3 Connectedness in CODWOR 113 5.4 Orthogonality in CODWOR 115 5.5 Latin Square Designs 116 5.6 Youden Square Design and Generalization 118 5.7 F-Squares 123 5.8 Lattice Square Designs 123 5.9 Analysis of CODWOR when the Units Effects Are Random 125 5.10 Numerical Example 127 5.11 Orthogonal Latin Squares 131 References 133 6. Cross-Over Designs with Residual Effects 135 6.1 Introduction 135 6.2 Analysis of CODWR 136 6.3 BRED 143 6.4 PBCOD(m) 148 6.5 Numerical Example 152 6.6 Analysis with Unit (or Subject) Effects Random 156 6.7 Concluding Remarks 159 References 160 7. Two-Period Cross-Over Designs with Residual Effects163 7.1 Introduction 163 7.2 Two-Period, Two-Treatment CODWR Analysis: Parametric Methods164 7.2.1 Analysis of the design based on the model (7.2.9) 167 7.2.2 Decomposition of the model (7.2.9) into intra- andinterunit components 169 7.2.3 Estimating direct effects contrast using cross-over natureof the treatments 170 7.2.4 Modified two-period, two-treatment design 171 7.2.5 Cost analysis 171 7.3 Two-Period, Two-Treatment CODWR Analysis: NonparametricMethods 173 7.4 Two-Period t Treatment Cross-Over Design 174 7.5 Numerical Examples 177 References 186 8. Other Cross-Over Designs with Residual Effects 189 8.1 Introduction 189 8.2 Extra-Period Designs 191 8.2.1 Residual effect of a treatment effect on itself is thesame as residual effect on other treatments 192 8.2.2 Residual effect of a treatment on itself is different fromthe residual effect on other treatments 193 8.3 Residual Effects Proportional to Direct Effects 194 8.4 Undiminished Residual Effects Designs 195 8.5 Treatment Balanced Residual Effects Designs 197 8.6 A General Linear Model for CODWR 199 8.7 Nested Design 201 8.8 Split-Plot Type CODWR 203 8.9 CODWR in Circular Arrangement 205 8.10 Numerical Examples 207 References 213 9. Some Constructions of Cross-Over Designs 215 9.1 Introduction 215 9.2 Galois Fields 215 9.3 Generalized Youden Designs 217 9.4 Williams' Balanced Residual Effects Designs 221 9.5 Other Balanced Residual Effects Designs 226 9.6 Combinatorially Overall Balanced Residual Effects Designs229 9.7 Construction of Treatment Balanced Residual Effects Designs231 9.8 Some Construction of PBCOD (m) 232 9.9 Construction of Complete Set of MOLS and Patterson'sBRED 234 9.10 Balanced Circular Arrangements 235 9.11 Concluding Remarks 236 References 237 Index 245ReviewsAuthor InformationDAMARAJU RAGHAVARAO, PhD, was Laura H. Carnell Professorand Chairperson in the Department of Statistics at TempleUniversity. With more than fifty years of research experience inall aspects of experimental design, sampling, and multivariateanalysis, Dr. Raghavarao authored eight additional books and over135 journal articles throughout his career. LAKSHMI PADGETT, PhD, is Senior Manager at JanssenR&D. Dr. Padgett has authored approximately twenty journalarticles, and her research interests include phase I, II, and IIItrials. Tab Content 6Author Website:Countries AvailableAll regions |