Empirical direction in design and analysis / Norman H. Anderson.

Format:

Book

Author/Creator:

Anderson, Norman H.

Language:

English

Subjects (All):

Psychometrics.

Psychology--Methodology.

Psychology.

Physical Description:

xv, 862 pages : illustrations ; 24 cm

Place of Publication:

Mahwah, N.J. : L. Erlbaum, 2001.

Summary:

The goal of this book is to help students develop skills of scientific inferences by the use of what Anderson calls "the experimental pyramid." He does not place the usual emphasis on null hypothesis testing, and also de-emphasizes computational formulas

Contents:

Chapter 1 Scientific Inference 1

1.1 Experimental Pyramid 2

1.2 Validity 8

1.3 Variability 16

1.4 Samples and Generality 20

1.5 Multiple Determination 25

Chapter 2 Statistical Inference 30

2.1 Sample and Population 31

2.2 Confidence Interval 33

2.3 Statistical Significance Test 41

2.4 Before and Beyond Significance Tests 47

Chapter 3 Elements of Anova-I 58

3.1 Algebraic Model for Anova 59

3.2 Significance Tests 61

3.3 Violations of Assumptions 68

Chapter 4 Elements of Anova-II 90

4.1 Confidence Intervals 91

4.2 Focused Comparisons 95

4.3 Power Analysis 102

Chapter 5 Factorial Design 118

5.1 Two-Factor Design 119

5.2 Interpreting Factorial Data 130

5.3 Three-Factor Design 139

Chapter 6 Repeated Measures Design 158

6.1 Subjects [times] Treatments, S [times] A Design 160

6.2 Multiple Repeated Measures 165

6.3 Mixed Designs 167

6.4 Beyond Overall Anova 171

6.5 Statistical Assumptions 175

Chapter 7 Understanding Interactions 188

7.1 Functions of Interactions 190

7.2 Measurement Theory and Interactions 193

7.3 Model Theory and Interactions 196

7.4 Interactionist Theories 200

7.5 High-Way Interactions 203

7.6 Perspective on Interactions 206

Chapter 8 Confounding 218

8.1 Categories of Confounding 221

8.2 Control of Confounding 244

Chapter 9 Regression and Correlation 258

9.1 One-Variable Regression 259

9.2 Correlation 274

Chapter 10 Frequency Data and Chi-Square 286

10.1 Elements of Chi-Square 288

10.2 Further Aspects of Chi-Square 295

Chapter 11 Single Subject Design 306

11.1 Validity and Reliability 308

11.2 Randomized Treatment Design 310

11.3 Serial Observation Design 312

11.4 Illustrative Single Subject Experiments 315

11.5 Methodology in Single Subject Design 333

Chapter 12 Nonnormal Data and Unequal Variance 350

12.1 Trimming 352

12.2 Distribution-Free Statistics 357

12.3 Outliers 361

12.4 Transformations 363

12.5 Anova with Unequal Variance 369

Chapter 13 Analysis of Covariance 382

13.1 Covariance with Random Groups 384

13.2 Covariance with Nonrandom Groups 390

Chapter 14 Design Topics I 400

14.1 Screening Subjects & Writing Instructions 401

14.2 Block Design 407

14.3 Latin Squares 415

14.4 Within Subjects & Between Subjects Design 425

Chapter 15 Design Topics II 442

15.1 Nested Factors and Natural Groups 443

15.2 Random Factors 446

15.3 Reducing Design Size 450

15.4 Unequal n 458

15.5 Field Science & Quasi-Experimental Design 464

Chapter 16 Multiple Regression 484

16.1 Multiple Regression 485

16.2 Interpretation with Observational Data 501

Chapter 17 Multiple Comparisons 524

17.1 The Twin Problems of [alpha] and [beta] 525

17.2 Familywise Procedures 531

17.3 Per Comparison Procedures 536

17.4 Problems in Multiple Comparisons 538

Chapter 18 Sundry Topics 550

18.1 Size and Importance of Effects 551

18.2 Contrast Analysis 559

18.3 Trend Analysis and Curve Shape 565

18.4 Seven Topics 572

Chapter 19 Foundations of Statistics 602

19.1 Foundations of Statistics 604

19.2 Functions of Significance Tests 624

19.3 Measurement Scales and Statistics 630

Chapter 20 Math Models for Process Analysis 646

20.1 Two Models for Addition Processes 647

20.2 Problems in Model Analysis 654

20.3 Signal Detection Theory 659

20.4 Issues in Model Analysis 670

20.5 Models as Base for Unified Theory 676

Chapter 21 Toward Unified Theory 688

21.1 Unified Theory 690

21.2 Functional Measurement Theory 691

21.3 Addition Model 697

21.4 Averaging Theory 705

21.5 Multiplication Model 711

21.6 Psychological Measurement Theory 716

21.7 Unified Theory 721

Chapter 22 Principles & Tactics for Writing 750

22.1 Five Principles 751

22.2 Tactics for Writing 755

22.3 Better Communication Skills 760

Chapter 23 Lifelong Learning 764

23.1 Empirical Direction in Learning

Teaching Statistics 765

23.2 Lifelong Learning 779

Chapter 0 Basic Statistical Concepts 782

0.2 Probability 793

0.3 Probability Thinking 795

0.4 Scientific Inference 802.

Notes:

Includes bibliographical references (pages 820-846) and indexes.

ISBN:

080583978X

OCLC:

46829034