Empirical Direction in Design and Analysis

by ;
Edition: 1st
Format: Hardcover
Pub. Date: 2001-07-01
Publisher(s): Psychology Pres
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Summary

The goal of Norman H. Anderson's new book is to help students develop skills of scientific inference. To accomplish this he organized the book around the "Experimental Pyramid"--six levels that represent a hierarchy of considerations in empirical investigation--conceptual framework, phenomena, behavior, measurement, design, and statistical inference. To facilitate conceptual and empirical understanding, Anderson de-emphasizes computational formulas and null hypothesis testing. Other features include: *emphasis on visual inspection as a basic skill in experimental analysis to help students develop an intuitive appreciation of data patterns; *exercises that emphasize development of conceptual and empirical application of methods of design and analysis and de-emphasize formulas and calculations; and *heavier emphasis on confidence intervals than significance tests. The book is intended for use in graduate-level experimental design/research methods or statistics courses in psychology, education, and other applied social sciences, as well as a professional resource for active researchers. The first 12 chapters present the core concepts graduate students must understand. The next nine chapters serve as a reference handbook by focusing on specialized topics with a minimum of technicalities.

Table of Contents

Scientific Inferencep. 1
Experimental Pyramidp. 2
Validityp. 8
Variabilityp. 16
Samples and Generalityp. 20
Multiple Determinationp. 25
Statistical Inferencep. 30
Sample and Populationp. 31
Confidence Intervalp. 33
Statistical Significance Testp. 41
Before and Beyond Significance Testsp. 47
Notesp. 53
Exercisesp. 54
Elements of Anova-Ip. 58
Algebraic Model for Anovap. 59
Significance Testsp. 61
Violations of Assumptionsp. 68
Notesp. 75
Appendixp. 77
Exercisesp. 84
Elements of Anova-IIp. 90
Confidence Intervalsp. 91
Focused Comparisonsp. 95
Power Analysisp. 102
Notesp. 111
Exercisesp. 113
Factorial Designp. 118
Two-Factor Designp. 119
Interpreting Factorial Datap. 130
Three-Factor Designp. 139
Notesp. 145
Appendixp. 148
Exercisesp. 151
Repeated Measures Designp. 158
Subjects [times] Treatments, S [times] A Designp. 160
Multiple Repeated Measuresp. 165
Mixed Designsp. 167
Beyond Overall Anovap. 171
Statistical Assumptionsp. 175
Notesp. 177
Exercisesp. 181
Understanding Interactionsp. 188
Functions of Interactionsp. 190
Measurement Theory and Interactionsp. 193
Model Theory and Interactionsp. 196
Interactionist Theoriesp. 200
High-Way Interactionsp. 203
Perspective on Interactionsp. 206
Notesp. 209
Exercisesp. 214
Confoundingp. 218
Categories of Confoundingp. 221
Control of Confoundingp. 244
Notesp. 250
Regression and Correlationp. 258
One-Variable Regressionp. 259
Correlationp. 274
Notesp. 280
Exercisesp. 282
Frequency Data and Chi-Squarep. 286
Elements of Chi-Squarep. 288
Further Aspects of Chi-Squarep. 295
Notesp. 300
Exercisesp. 302
Single Subject Designp. 306
Validity and Reliabilityp. 308
Randomized Treatment Designp. 310
Serial Observation Designp. 312
Illustrative Single Subject Experimentsp. 315
Methodology in Single Subject Designp. 333
Notesp. 338
Exercisesp. 345
Nonnormal Data and Unequal Variancep. 350
Trimmingp. 352
Distribution-Free Statisticsp. 357
Outliersp. 361
Transformationsp. 363
Anova with Unequal Variancep. 369
Notesp. 373
Exercisesp. 378
Analysis of Covariancep. 382
Covariance with Random Groupsp. 384
Covariance with Nonrandom Groupsp. 390
Notesp. 395
Exercisesp. 397
Design Topics Ip. 400
Screening Subjects and Writing Instructionsp. 401
Block Designp. 407
Latin Squaresp. 415
Within Subjects and Between Subjects Designp. 425
Notesp. 431
Exercisesp. 437
Design Topics IIp. 442
Nested Factors and Natural Groupsp. 443
Random Factorsp. 446
Reducing Design Sizep. 450
Unequal np. 458
Field Science and Quasi-Experimental Designp. 464
Notesp. 475
Exercisesp. 481
Multiple Regressionp. 484
Multiple Regressionp. 485
Interpretation with Observational Datap. 501
Notesp. 514
Exercisesp. 520
Multiple Comparisonsp. 524
The Twin Problems of [alpha] and [beta]p. 525
Familywise Proceduresp. 531
Per Comparison Proceduresp. 536
Problems in Multiple Comparisonsp. 538
Notesp. 546
Exercisesp. 548
Sundry Topicsp. 550
Size and Importance of Effectsp. 551
Contrast Analysisp. 559
Trend Analysis and Curve Shapep. 565
Seven Topicsp. 572
Notesp. 589
Exercisesp. 596
Foundations of Statisticsp. 602
Foundations of Statisticsp. 604
Functions of Significance Testsp. 624
Measurement Scales and Statisticsp. 630
Notesp. 637
Math Models for Process Analysisp. 646
Two Models for Addition Processesp. 647
Problems in Model Analysisp. 654
Signal Detection Theoryp. 659
Issues in Model Analysisp. 670
Models as Base for Unified Theoryp. 676
Notesp. 677
Exercisesp. 681
Toward Unified Theoryp. 688
Unified Theoryp. 690
Functional Measurement Theoryp. 691
Addition Modelp. 697
Averaging Theoryp. 705
Multiplication Modelp. 711
Psychological Measurement Theoryp. 716
Unified Theoryp. 721
Notesp. 729
Exercisesp. 742
Principles and Tactics for Writingp. 750
Five Principlesp. 751
Tactics for Writingp. 755
Better Communication Skillsp. 760
Notesp. 761
Lifelong Learningp. 764
Empirical Direction in Learning--Teaching Statisticsp. 765
Lifelong Learningp. 779
Notesp. 780
Basic Statistical Conceptsp. 782
Basic Conceptsp. 783
Probabilityp. 793
Probability Thinkingp. 795
Scientific Inferencep. 802
Notesp. 803
Exercisesp. 805
Tablesp. 808
Referencesp. 820
Author Indexp. 847
Subject Indexp. 854
Table of Contents provided by Syndetics. All Rights Reserved.

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