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Experimental Designs Using ANOVA (with Student Suite CD-ROM) New edition [Hardback]

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  • Formāts: Hardback, 745 pages, Illustrations
  • Izdošanas datums: 08-Mar-2006
  • Izdevniecība: Brooks/Cole
  • ISBN-10: 0534405142
  • ISBN-13: 9780534405144
Citas grāmatas par šo tēmu:
  • Formāts: Hardback, 745 pages, Illustrations
  • Izdošanas datums: 08-Mar-2006
  • Izdevniecība: Brooks/Cole
  • ISBN-10: 0534405142
  • ISBN-13: 9780534405144
Citas grāmatas par šo tēmu:
Written for those with basic descriptive and inferential statistics, this text is designed for senior-level undergraduates and first-year graduate students. The authors take an innovative regressive approach to ANOVA alongside the traditional approach. They begin with the nature of research, types of research designs, types of treatments, outcome measures, issues encountered in most designs, generalizing results, computer assistance. They cover organizing, describing and screening data; the logic of analysis and tests of assumptions in basic ANOVA; one-way randomized-groups analysis of variance and fixed-effects designs; factorial randomized-groups and fixed-effects designs; repeated measure designs, mixed randomized-repeated designs; analysis of covariance; Latin-square designs; screening and other incomplete designs; and analysis with random effects. Problem sets come with each chapter. The CD-ROM contains data sets and the student solutions manual. Annotation ©2006 Book News, Inc., Portland, OR (booknews.com)

Succeed in statistics with EXPERIMENTAL DESIGN USING ANOVA with accompanying STUDENT SUITE CD-ROM! With a practical approach, this statistics text provides you with instructions on how to perform both simple and complex analyses by hand, through regression, and through SPSS and SAS so that you will be prepared to effectively design and analyze research projects. Examples and exercises found throughout the text help clarify difficult concepts. Use the accompanying CD-ROM and the book-specific website to access data sets for these examples and exercises. All chapters follow a similar outline allowing you to readily and easily find the material you are looking for.

This text reflects the practical approach of the authors. Barbara Tabachnick and Linda Fidell emphasize the use of statistical software in design and analysis of research in addition to conceptual understanding fostered by the presentation and interpretation of fundamental equations. EXPERIMENTAL DESIGN USING ANOVA includes the regression approach to ANOVA alongside the traditional approach, making it clearer and more flexible. The text includes details on how to perform both simple and complicated analyses by hand through traditional means, through regression, and through SPSS and SAS.
Preface xix
Introduction
1(28)
The Nature of Research
2(4)
IVs and DVs
2(1)
What Is an Experiment?
2(2)
What If It Isn't an Experiment?
4(1)
Relationship between Design and Analysis
5(1)
Monitoring Processes to Aid in Experimental Design
6(1)
Types of Research Designs
6(5)
Randomized-Groups Designs
6(1)
Repeated-Measures Designs
7(1)
One-Way and Factorial Designs
8(1)
Blocking Designs
9(1)
Crossing and Nesting
9(2)
Types of Treatments
11(1)
Qualitative IVs
11(1)
Quantitative IVs
11(1)
Outcome Measures
12(1)
Types of Outcome Measures
12(1)
Number of Outcome Measures
13(1)
Overview of Research Designs
13(4)
Continuous Outcomes
13(3)
Rank Order Outcome
16(1)
Discrete Outcomes
16(1)
Time as an Outcome
17(1)
Overview of Issues Encountered in Most Designs
17(4)
Statistical Inference
17(2)
Power
19(1)
Effect Size
20(1)
Parameter Estimates
20(1)
To Test or Not to Test?
21(1)
Generalizing Results
21(1)
Computer Assistance
22(2)
Programs for Statistical Analysis
22(2)
Programs for Designing Experiments
24(1)
Organization of the Book
24(1)
Choosing a Design: Some Guidelines
25(2)
Problem Sets
27(2)
Organizing Describing, and Screening
29(40)
Organizing Data for a Computer
29(4)
Discrete, Continuous, and Ordinal Data
30(1)
Randomized-Groups Designs
31(1)
Repeated-Measures Designs
32(1)
Describing Data from One Variable
33(20)
Discrete Variables
34(1)
Ordinal Variables
35(2)
Continuous Variables
37(16)
Describing Relationships between Two Variables
53(14)
Both Variables Discrete
53(3)
Both Variables Continuous
56(4)
One Discrete and One Continuous Variable
60(7)
Problem Sets
67(2)
Basic ANOVA: Logic of Analysis and Tests of Assumptions
69(29)
Introduction
69(1)
Analysis of Variance
70(12)
The General Linear Model
70(1)
Generation of a Data Set
71(2)
The Basic Analysis
73(9)
The Regression Approach to ANOVA
82(4)
Birariate Regression and Basic ANOVA
82(4)
Why Bother?
86(1)
Assumptions of Analysis
86(4)
Normality of Sampling Distribution of Means
86(1)
Independence of Errors
87(1)
Homogeneity of Variance
88(1)
Absence of Outliers
89(1)
Other Recurring Issues
90(6)
Effect Size
90(1)
Power
91(1)
Comparisons
91(1)
Orthogonality
92(1)
Coding
92(1)
Missing Values
93(1)
Transformations
94(2)
Overview of Remaining
Chapters
96(1)
Problem Sets
97(1)
One-Way Randomized-Groups Analysis of Variance, Fixed-Effects Designs
98(56)
General Purpose and Description
98(1)
Kinds of Research Questions
99(2)
Effect of the IV
100(1)
Specific Comparisons
100(1)
Parameter Estimates
100(1)
Effect Sizes
101(1)
Power
101(1)
Assumptions and Limitations
101(1)
Theoretical Issues
101(1)
Practical Issues
102(1)
Fundamental Equations
102(9)
Allocation of Cases
102(1)
Partition of Variance
103(1)
Traditional ANOVA Approach (Three Levels)
103(1)
Regression Approach (Three Levels)
104(4)
Computer Analyses of Small-Sample One-Way Design
108(3)
Some Important Issues
111(29)
Effect Size
111(4)
Power and Sample Size
115(5)
Unequal Sample Sizes
120(2)
Homogeneity of Variance
122(1)
Specific Comparisons
123(17)
Complete Example of One-Way ANOVA
140(8)
Evaluation of Assumptions
141(2)
Planned Trend Analysis for One Way Randomized-Groups Design
143(5)
Comparison of Programs
148(3)
SPSS Package
148(1)
SAS System
148(3)
SYSTAT System
151(1)
Problem Sets
151(3)
Factorial Randomized-Groups, Fixed-Effects Designs
154(88)
General Purpose and Description
154(1)
Kinds of Research Questions
155(3)
Effects of the IVs
155(1)
Effect of Interactions among IVs
156(1)
Specific Comparisons
156(1)
Parameter Estimates
157(1)
Effect Sizes
157(1)
Power
157(1)
Assumptions and Limitations
158(1)
Theoretical Issues
158(1)
Practical Issues
158(1)
Fundamental Equations
159(15)
Allocation of Cases
160(1)
Partition of Sources of Variance
161(2)
Traditional ANOVA Approach (3 X 3)
163(2)
Regression Approach (3 X 3)
165(5)
Computer Analyses of Small-Sample Factorial Design
170(4)
Other Types of Randomized-Groups Designs
174(7)
Higher-Order Factorial Designs
175(5)
Factorial Design with a Single Control
180(1)
Some Important Issues
181(40)
Interpreting Interactions
181(6)
Effect Size
187(3)
Power and Sample Size
190(2)
Specific Comparisons
192(24)
Unequal Sample Sizes
216(5)
Complete Example of Two-Way Randomized-Groups ANOVA
221(15)
Evaluation of Assumptions
221(4)
Randomized-Groups Analysis of Variance
225(11)
Comparison of Programs
236(4)
SPSS Package
236(3)
SAS System
239(1)
SYSTAT System
239(1)
Problem Sets
240(2)
Repeated-Measures Designs
242(74)
General Purpose and Description
242(1)
Kinds of Research Questions
243(2)
Effect of the IVs
244(1)
Effect of Interactions among IVs
244(1)
Parameter Estimates
244(1)
Effect Sizes
244(1)
Power
245(1)
Specific Comparisons
245(1)
Assumptions and Limitations
245(4)
Theoretical Issues
245(1)
Practical Issues
246(3)
Fundamental Equations
249(31)
One-Way Repeated-Measures ANOVA
249(12)
Factorial Repeated-Measures Designs
261(19)
Types of Repeated-Measures Designs
280(2)
Time as a Variable
280(1)
Simultaneous Repeated Measures
281(1)
Matched Randomized Blocks
281(1)
Some Important Issues
282(20)
Carryover Effects: Control of Extraneous Variables
282(2)
Assumptions of Analysis: Independence of Errors, Sphericity, Additivity, and Symmetry
284(4)
Power, Sample Size, and Relative Efficiency
288(1)
Effect Size
289(2)
Missing Data
291(1)
Specific Comparisons
292(10)
Complete Example of Two-Way Repeated-Measures ANOVA
302(10)
Evaluation of Assumptions
302(2)
Planned Trend Analysis of Two-Way Repeated-Measures Design
304(8)
Comparison of Programs
312(2)
SPSS Package
312(1)
SAS System
313(1)
SYSTAT System
313(1)
Problem Sets
314(2)
Mixed Randomized-Repeated Designs
316(63)
General Purpose and Description
316(2)
Kinds of Research Questions
318(1)
Effects of the IVs
318(1)
Effects of Interactions among IVs
318(1)
Parameter Estimates
318(1)
Effect Sizes
318(1)
Power
318(1)
Specific Comparisons
319(1)
Assumptions and Limitations
319(2)
Theoretical Issues
319(1)
Practical Issues
319(2)
Fundamental Equations
321(17)
Allocation of Cases
321(1)
Partition of Sources of Variance
322(2)
Traditional ANOVA for the Mixed Design
324(3)
Regression Approach to the Mixed Design
327(5)
Computer Analyses of Small-Sample Mixed Design
332(6)
Types of Mixed Designs
338(2)
The Pretest-Posttest Design
338(1)
Expanding Mixed Designs
338(2)
Some Important Issues
340(15)
Comparisons on the Margins
340(5)
Simple Main Effects Analysis
345(3)
Simple Comparisons
348(1)
Interaction Contrasts
349(2)
Comparisons through the Regression Approach
351(4)
Complete Example of Mixed Randomized-Repeated ANOVA
355(14)
Evaluation of Assumptions
356(2)
Three-Way Mixed Randomized-Repeated ANOVA
358(11)
Comparison of Programs
369(2)
SPSS Package
369(1)
SAS System
370(1)
SYSTAT System
370(1)
Putting It All Together for Factorial Designs
371(6)
Allocation of Cases
371(1)
Assumptions of Analysis
371(1)
Error Terms
371(2)
Setup for Regression
373(3)
Developing Computational Equations from Degrees of Freedom
376(1)
Problem Sets
377(2)
Analysis of Covariance
379(99)
General Purpose and Description
379(3)
Kinds of Research Questions
382(2)
Effect of the IV(s)
382(1)
Effect of Interactions among IVs
383(1)
Effect of Covariates
383(1)
Parameter Estimates
383
Effect Sizes
333(51)
Power
384(1)
Specific Comparisons
384(1)
Assumptions and Limitations
384(6)
Theoretical Issues
384(1)
Practical Issues
385(5)
Fundamental Equations
390(11)
Allocation of Cases to Conditions
390(1)
Partition of Sources of Variance
390(2)
Traditional Approach with Three Levels and One Covariate
392(2)
Computer Analyses of Small-Sample ANCOVA
394(5)
Computer Analysis Using Regression Approach to ANCOVA
399(2)
Types of Designs Using Covariates
401(11)
Randomized-Groups Factorial
401(1)
Repeated Measures
402(10)
Some Important Issues
412(20)
Multiple Covariates
412(6)
Test of Homogeneity of Regression
418(5)
Effect Size
423(1)
Power
424(1)
Adjusted Means
424(2)
Specific Comparisons
426(4)
Alternatives to ANCOVA
430(2)
Complete Examples of Analysis of Covariance
432(41)
One-Way Analysis of Covariance with Five Levels and One Covariate
432(9)
Mixed Randomized-Groups and Repeated-Measures Analysis of Covariance
441(32)
Comparison of Programs
473(2)
SPSS Package
473(1)
SAS System
473(2)
SYSTAT System
475(1)
Problem Sets
475(3)
Latin-Square Designs
478(74)
General Purpose and Description
478(3)
Kinds of Research Questions
481(2)
Effects of the IV(s)
481(1)
Interactions among IVs
482(1)
Parameter Estimates
482(1)
Effect Sizes and Power
482(1)
Specific Comparisons
483(1)
Assumptions and Limitations
483(2)
Theoretical Issues
483(1)
Practical
483(2)
Fundamental Equations
485(11)
Allocation of Cases
486(1)
Partition of Sources of Variance
486(2)
Traditional ANOVA Approach to 3 X 3 X 3 Latin Square
488(2)
Regression Approach to 3 X 3 X 3 Latin Square
490(2)
Analyses of Small-Sample Latin Square Example
492(4)
Types of Latin-Square
496(22)
Replicated Randomized-Groups Designs
497(4)
Replicated Repeated-Measures Designs
501(11)
Less Commonly Encountered Designs
512(6)
Some Important Issues
518(10)
Sphericity in Repeated-Measures Designs
519(2)
Choosing a Latin Square
521(1)
Power, Effect Size, and Relative Efficiency
522(3)
Specific Comparisons
525(2)
Missing Data
527(1)
Complete Examples of Latin-Square ANOVA
528(20)
Complete Example of 4 X 4 X 4 Randomized-Groups Latin-Square Analysis
528(9)
Complete Example of a Repeated-Measures Crossover Design with Multiple Trials
537(11)
Comparison of Programs
548(1)
SPSS Package
549(1)
SAS System
549(1)
SYSTAT System
549(1)
Problem Sets
549(3)
Screening and Other Incomplete Designs
552(68)
General Purpose and Description
552(2)
Kinds of Research Questions
554(1)
Effects of the IV(s)
554(1)
Effects of Interactions among IV(s)
554(1)
Parameter Estimates
554(1)
Effect Sizes and Power
555(1)
Specific Comparisons
555(1)
Assumptions and Limitations
555(2)
Theoretical Issues
555(1)
Practical Issues
556(1)
Fundamental Equations
557(12)
Allocation of Cases
558(1)
Partition of Sources of Variance
559(1)
Regression Approach to a 25 Half-Factorial ANOVA
560(5)
Computer Analyses of the Small-Sample 25-1 Half-Factorial ANOVA
565(4)
Types of Screening and Other Incomplete Designs
569(29)
Resolution of Incomplete Designs
569(1)
Fractional-Factorial Designs
569(6)
Plackett-Burman Designs
575(2)
Taguchi Designs
577(6)
Response-Surface Methodology
583(12)
Optimal Designs
595(3)
Some Important Issues
598(7)
Generating Screening and Other Incomplete Designs
598(5)
Choosing among Screening and Other Incomplete Designs
603(2)
Complete Example of a Central-Composite Design
605(8)
Generating the Design
606(1)
Assumptions and Limitations
606(3)
Three-Factor Central-Composite Design
609(4)
Comparisons of Programs
613(4)
SAS ADX
616(1)
NCSS Design of Experiments
617(1)
Problem Sets
617(3)
Analysis of Variance with Random Effects
620(65)
General Purpose and Description
620(3)
Kinds of Research Questions
623(2)
Effect of the IV(s)
623(1)
Effects of Interactions among IVs
623(1)
Specific Comparisons
623(1)
Parameter Estimates
623(1)
Effect Sizes
624(1)
Power
624(1)
Assumptions and Limitations
625(2)
heoretical Issues
625(1)
Practical Issues
626(1)
Fundamental Equations
627(11)
Allocation of Cases
627(1)
Partition of Sources of Variance
628(2)
Traditional ANOVA Approach (One Treatment Factor and One Level of Nesting)
630(2)
Regression Approach. (One Treatment Factor and One Level of Nesting)
632(1)
Computer Analyses of Small-Sample Nested Example
632(6)
Types of Designs with Random Effects
638(18)
Nested Designs
638(6)
One-Way Random-Effects Design
644(1)
Factorial Random-Effects Designs
644(4)
Mixed Fixed-Random Designs
648(8)
Some Important Issues
656(12)
Error Terms in Random-Effects ANOVA
657(5)
Alternative Strategies to ANOVA
662(2)
Trend Analysis with Unequal Spacing
664(3)
Homogeneity of Covariance
667(1)
Effect Size
668(1)
Complete Example of Random-Effects Anova
668(12)
Evaluation of Assumptions
669(7)
ANOVA for Doubly Nested Design
676(4)
Comparison of Programs
680(3)
SAS System
680(2)
SPSS Package
682(1)
SYSTAT System
683(1)
Problem Sets
683(2)
A Statistical Tables
685(15)
Critical Values of F Distribution
686(7)
Critical Values of X2 Distribution
693(1)
Critical Values of Studentized Range Statistic Distribution
694(2)
Critical Values of Dunnett's d-Statistic in Comparing Treatment Means with a (1-sided test)
696(2)
Coefficients of Orthogonal Polynomials
698(1)
Critical Values of Fmax
699(1)
Appendix B Research Designs for Complete Examples
700(6)
Facets in Fly's Eyes
700(1)
Bonding Strength of Periodontal Dressings
701(1)
Reaction Time to Identify Figures
702(1)
Auto Pollution Filter Noise
702(1)
Wear Testing of Fabric Samples
703(1)
Odors and Performance
703(1)
Processing Time for ANOVA
704(1)
Nambeware Polishing Times
704(1)
Chest Deceleration Injuries in Automobile Crashes
705(1)
Fat Content of Eggs
705(1)
References 706(5)
Index 711