Experiment Design and Statistical Methods For

Experiment Design and Statistical Methods introduces the concepts, principles, and techniques for carrying out a practical research project either in real world settings or laboratories - relevant to studies in psychology, education, life sciences, social sciences, medicine, and occupational and management research.The text covers:· repeated measures· unbalanced and non-randomized experiments and surveys· choice of design· adjustment for confounding variables· model building and partition of variance· covariance· multiple regressionExperiment Design and Statistical Methods contains a unique extension of the Venn diagram for understanding non-orthogonal design, and it includes exercises for developing the reader's confidence and competence. The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM.

Preface

Part One: Statistical Design and Analysis for Basic Experiments

1

(98)

1 Introduction

3

(3)

1.1 Structure and scope of Part One

3

(1)

1.2 Inference for descriptive and experimental research

3

(1)

1.3 What is experimental research?

4

(1)

1.4 Theory testing, generalization and cost-effectiveness

5

(1)

2 Introduction to four basic designs

6

(11)

2.1 Single-factor independent groups design

6

(2)

2.2 Single-factor repeated measures design

8

(2)

2.3 Two-factor design

10

(4)

2.4 Single-factor independent groups design with use of covariate

14

(3)

3 Overview of concepts and techniques

17

(9)

3.1 Variance

17

(1)

3.2 Variance of means

18

(1)

3.3 Random sampling and randomization

19

(1)

3.4 Confidence intervals

20

(1)

3.5 Sampling fluctuation and sampling error

20

(1)

3.6 Statistical significance

21

(1)

3.7 Formulating decision-making as a test of hypotheses

21

(2)

3.8 Power

23

(1)

3.9 Sensitivity

24

(1)

3.10 Efficiency

24

(1)

3.11 Bias

25

(1)

3.12 Logistical constraints

25

(1)

4 Single-factor independent groups design

26

(12)

4.1 Introduction

26

(1)

4.2 The principles of the analysis of variance

26

(2)

4.3 Analysis of variance and significance test

28

(3)

4.4 The summary table and the decomposition of the total SS

31

(2)

4.5 Computational formulae for degrees of freedom and SSs

33

(1)

4.6 Underlying model and assumptions for tests of significance

34

(1)

4.7 Concept linkage for analysis of variance

35

(1)

4.8 Exercises

36

(2)

5 Single-factor repeated measures design

38

(12)

5.1 Introduction

38

(1)

5.2 Variation present in the repeated measures design

38

(2)

5.3 The principles of the analysis of variance

40

(1)

5.4 Analysis of variance and significance test

41

(4)

5.5 Computational formulae for SS and degrees of freedom

45

(1)

5.6 Underlying model and assumptions for tests of significance

46

(1)

5.7 Exercises

47

(3)

6 Two-factor independent groups design

50

(18)

6.1 Introduction

50

(1)

6.2 Example of two-factor design

50

(3)

6.3 The effect of the interaction of the factors

53

(2)

6.4 The principles of the analysis of variance

55

(5)

6.5 The summary table and tests of significance

60

(2)

6.6 Formulae for hand calculation of SSs

62

(3)

6.7 Underlying model and assumptions for tests of significance

65

(1)

6.8 Exercises

65

(3)

7 Single-factor independent groups design with covariate

68

(8)

7.1 Introduction

68

(1)

7.2 The concept and technique of covariate adjustment

68

(2)

7.3 The effect of covariate adjustment on variance estimates

70

(3)

7.4 Underlying model and assumptions for tests of significance

73

(1)

7.5 Exercises

74

(2)

8 Contrasts and comparisons among means

76

(8)

8.1 Introduction

76

(1)

8.2 Formulating and testing a comparison among means

76

(4)

8.3 A posteriori tests of comparisons

80

(2)

8.4 Overview of decisions for contrasts and comparisons of means

82

(1)

8.5 Exercises

83

(1)

9 Power and sensitivity in design decisions

84

(15)

9.1 Introduction

84

(1)

9.2 Sensitivity and efficiency gains from a continuous covariate

84

(2)

9.3 Sensitivity and efficiency gains from a category covariate

86

(3)

9.4 Choice of sample size

89

(4)

9.5 Choice of within- or between-subjects design

93

(2)

9.6 Summary of influences on design decisions

95

(1)

9.7 Exercises

95

(4)

Part Two: Unbalanced, Non-Randomized and Survey Designs

99

(44)

10 Unbalanced and confounded designs

101

(29)

10.1 Introduction

101

(1)

10.2 Two-factor unbalanced design

102

(11)

10.3 Confounding in one-variable non-randomized designs

113

(12)

10.4 Exercises

125

(5)

11 Multiple regression

130

(13)

11.1 Introduction

130

(1)

11.2 Overview of designs, variables and orthogonality

130

(1)

11.3 Comparison of models with category and continuous independent variables

131

(7)

11.4 Glossary of terms for multiple regression

138

(1)

11.5 Sequential model construction

139

(3)

11.6 Exercises

142

(1)

Part Three: Analysis for Further Experiment Designs

143

(43)

12 Two-factor designs with between- and within-subjects factors

145

(16)

12.1 Introduction

145

(1)

12.2 Example of a BW design

145

(4)

12.3 Example of a WW design

149

(2)

12.4 Overview of rules for the ANOVA summary table for designs BB, BW and WW

151

(2)

12.5 Tests of significance for simple effects in BW and WW designs

153

(3)

12.6 Calculation pro forma for simple effects in two-factor designs

156

(1)

12.7 Contrasts and comparisons in the BW and WW designs

157

(1)

12.8 Exercises

158

(3)

13 Three-factor designs

161

(25)

13.1 Introduction

161

(1)

13.2 Example of a BBB design

162

(7)

13.3 Example of a BBW design

169

(1)

13.4 Example of a BWW design

170

(3)

13.5 Summary of rules for analysis of BBB, BBW, BWW and WWW designs

173

(10)

13.6 Exercises

183

(3)

Appendix A: Hints on use of computer programs

186

(2)

Appendix B: Additional exercises for Chapters 5-13

188

(28)

Appendix C: Solutions to exercises for Chapters 4-13

216

(25)

Appendix D: Approximate degrees of freedom for test of significance for simple effects in BW and WW designs

241

(1)

Appendix E: Rationale for approximate sample size formula

242

(1)

Appendix F: Tables of critical values

243

(15)

References

258

(1)

Index

259

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Experiment Design and Statistical Methods For Behavioural and Social Research

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Experiment Design and Statistical Methods For Behavioural and Social Research

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