Repeated Measures Design for Empirical Researchers

Informationen zum Autor J. P. Verma, PhD, is Professor of Statistics and Director of the Center for Advanced Studies at Lakshmibai National Institute of Physical Education, India. Professor Verma is an active researcher in sports modeling and data analysis and has conducted many workshops on research methodology, research designs, multivariate analysis, statistical modeling, and data analysis for students of management, physical education, social science, and economics. He is author of Statistics for Exercise Science and Health with Microsoft(r) Office Excel(r), also published by Wiley. Klappentext Introduces the applications of repeated measures design processes with the popular IBM SPSS(r) softwareRepeated Measures Design for Empirical Researchers presents comprehensive coverage of the formation of research questions and the analysis of repeated measures using IBM SPSS and also includes the solutions necessary for understanding situations where the designs can be used. In addition to explaining the computation involved in each design, the book presents a unique discussion on how to conceptualize research problems as well as identify appropriate repeated measures designs for research purposes.Featuring practical examples from a multitude of domains, including psychology, the social sciences, management, and sports science, the book helps readers better understand the associated theories and methodologies of repeated measures design processes. The book covers various fundamental concepts involved in the design of experiments, basic statistical designs, computational details, differentiating independent and repeated measures designs, and testing assumptions. Along with an introduction to IBM SPSS software, Repeated Measures Design for Empirical Researchers includes:* A discussion of the popular repeated measures designs frequently used by researchers such as two-way repeated measures design, two-way mixed design, one-way repeated measures ANOVA, and mixed design with two-way MANOVA* Coverage of sample size determination for the successful implementation of designing and analyzing a repeated measures study* A step-by-step guide to analyzing the data obtained with real-world examples throughout to illustrate the underlying advantages and assumptions* A related website with supplementary IBM SPSS data sets and programming solutions as well as additional case studiesRepeated Measures Design for Empirical Researchers is a useful textbook for graduate- and PhD-level students majoring in biostatistics, the social sciences, psychology, medicine, management, sports, physical education, and health. The book is also an excellent reference for professionals interested in experimental designs and statistical sciences as well as statistical consultants and practitioners from other fields including biological, medical, agricultural, and horticultural sciences.J. P. Verma, PhD, is Professor of Statistics and Director of the Center for Advanced Studies at Lakshmibai National Institute of Physical Education, India. Professor Verma is an active researcher in sports modeling and data analysis and has conducted many workshops on research methodology, research designs, multivariate analysis, statistical modeling, and data analysis for students of management, physical education, social science, and economics. He is author of Statistics for Exercise Science and Health with Microsoft(r) Office Excel(r), also published by Wiley. Zusammenfassung Discusses how to conceptualize research problems as well as identify appropriate repeated measures designs for research purposes. In this book, examples have been chosen from multiple domains, including psychology, the social sciences, management, and sports science, to aid readers in understanding both the associated theories and methodologies. Inhaltsverzeichnis Preface xv1 Foundations of Experimental Design 1Introduction 1What is Experimental Research? ...

Table des matières

Preface xv
 
1 Foundations of Experimental Design 1
 
Introduction 1
 
What is Experimental Research? 2
 
Design of Experiment and its Principles 3
 
Randomization 3
 
Replication 4
 
Blocking 4
 
Statistical Designs 5
 
Completely Randomized Design 5
 
Randomized Block Design 6
 
Matched Pairs Design 8
 
Latin Square designs 8
 
Factorial Experiment 9
 
Terminologies in Design of Experiment 10
 
Subject 11
 
Experimental Unit 11
 
Factor and Treatment 11
 
Criterion Variable 12
 
Variation and Variance 12
 
Experimental Error 12
 
External Validity 13
 
Internal Validity 13
 
Considerations in Designing an Experiment 13
 
Systematic Variance 14
 
Extraneous Variance 14
 
Randomization Method 15
 
Elimination Method 15
 
Matching Group Method 15
 
Adding Additional Independent Variable 16
 
Statistical Control 16
 
Error Variance 17
 
Exercise 17
 
Assignment 18
 
Bibliography 18
 
2 Analysis of Variance and Repeated Measures Design 21
 
Introduction 21
 
Understanding Variance and Sum of Squares 22
 
One Way Analysis of Variance for Independent Measures Design 24
 
Assumptions 24
 
Illustration I 25
 
Partitioning of Total Variation in the Design 26
 
Computation 26
 
Explanation 27
 
Partitioning of SS and Degrees of Freedom 27
 
Computation 27
 
Results 29
 
Post-Hoc Analysis 29
 
Means Plot 31
 
Repeated Measures Design 31
 
When to Use Repeated Measures ANOVA 32
 
Assumptions 32
 
Solving Repeated Measures Design With One-Way ANOVA 33
 
Illustration II 34
 
Hypothesis Construction 34
 
Layout Design 35
 
One-Way Repeated Measures ANOVA Model 36
 
Computation in Repeated Measures Design with One-Way ANOVA 36
 
Explanation 37
 
Computation 37
 
Testing Sphericity Assumption 39
 
Correcting for Degrees of Freedom 41
 
Results 43
 
Pair-Wise Comparison of Means 43
 
Bonferroni Correction 44
 
Effect Size 45
 
Exercise 46
 
Assignment 47
 
Bibliography 48
 
3 Testing Assumptions in Repeated Measures Design Using SPSS 51
 
Introduction 51
 
First Step in Using SPSS 52
 
Assumptions 53
 
Testing Normality 54
 
Test of Normality 57
 
Q-Q Plot for Normality 57
 
Box-plot for Identifying Outliers 59
 
Testing Sphericity 60
 
Remedial Measures when Assumption Fails 62
 
Transforming Nonnormal Data into Normal 62
 
Choice of Design and Sphericity 63
 
Sample Size Determination 64
 
Important Terms 64
 
Confidence Interval 64
 
Confidence Level 65
 
Power of the Test 66
 
Sample Size Determination on the Basis of Cost 67
 
Sample Size Determination on the Basis of Accuracy Factor 67
 
Sample Size in Estimating Mean 67
 
Sample Size in Hypothesis Testing 68
 
Exercise 68
 
Assignment 69
 
Bibliography 70
 
4 One-Way Repeated Measures Design 73
 
Introduction to Design 73
 
Advantage of One-Way Repeated Measures Design 74
 
Weakness of Repeated Measures Design 74
 
Application 74
 
Layout Design 75
 
Case I: When the Levels of Within-Subjects Variable are Different Tre

Détails du produit

• Auteurs: Verma, Dr. J. P. Verma, J P Verma, J. P. Verma, Jp Verma
• Edition: Wiley, John and Sons Ltd
• Langues: Anglais
• Format d'édition: Livre Relié
• Sortie: 22.09.2015
• EAN: 9781119052715
• ISBN: 978-1-119-05271-5
• Pages: 288
• Catégories: Sciences naturelles, médecine, informatique, technique > Mathématiques > Théorie des probabilités, stochastique, statistiques; Sciences sociales, droit, économie > Sociologie > Théories sociologiques; Statistik, Psychologie, Statistics, Psychology, VERSUCHSPLANUNG, Experimental Design, Psychologische Methoden, Forschung u. Statistik, Psychological Methods, Research & Statistics, Statistical Software / SPSS, Statistiksoftware / SPSS