Damaraju Raghavarao, Lakshmi Padgett

Repeated Measurements

• Gebundenes Buch

Produktbeschreibung

An introduction to state-of-the-art experimental design approaches to better understand and interpret repeated measurement data in cross-over designs.

Repeated Measurements and Cross-Over Designs:
Features the close tie between the design, analysis, and presentation of results
Presents principles and rules that apply very generally to most areas of research, such as clinical trials, agricultural investigations, industrial procedures, quality control procedures, and epidemiological studies
Includes many practical examples, such as PK/PD studies in the pharmaceutical industry, k-sample and one sample repeated measurement designs for psychological studies, and residual effects of different treatments in controlling conditions such as asthma, blood pressure, and diabetes.
Utilizes SAS(R) software to draw necessary inferences. All SAS output and data sets are available via the book's related website.

This book is ideal for a broad audience including statisticians in pre-clinical research, researchers in psychology, sociology, politics, marketing, and engineering.

Produktdetails

• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 272
• Erscheinungstermin: 14. April 2014
• Englisch
• Abmessung: 236mm x 157mm x 20mm
• Gewicht: 499g
• ISBN-13: 9781118709252
• ISBN-10: 111870925X
• Artikelnr.: 39562420

Autorenporträt

DAMARAJU RAGHAVARAO, PhD, was Laura H. Carnell Professor and Chairperson in the Department of Statistics at Temple University. With more than fifty years of research experience in all aspects of experimental design, sampling, and multivariate analysis, Dr. Raghavarao authored eight additional books and over 135 journal articles throughout his career. LAKSHMI PADGETT, PhD, is Senior Manager at Janssen R&D. Dr. Padgett has authored approximately twenty journal articles, and her research interests include phase I, II, and III trials.

Inhaltsangabe

Preface 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 Sphericity Condition 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
Effects 163 7.1 Introduction 163 7.2 Two-Period, Two-Treatment CODWR
Analysis: Parametric Methods 164 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- and
interunit components 169 7.2.3 Estimating direct effects contrast using
cross-over nature of 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: Nonparametric Methods 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 the same as residual effect on other treatments 192 8.2.2
Residual effect of a treatment on itself is different from the 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 Designs 229 9.7
Construction of Treatment Balanced Residual Effects Designs 231 9.8 Some
Construction of PBCOD (m) 232 9.9 Construction of Complete Set of MOLS and
Patterson's BRED 234 9.10 Balanced Circular Arrangements 235 9.11
Concluding Remarks 236 References 237 Index 245