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E-raamat: Levine's Guide to SPSS for Analysis of Variance 2nd edition [Taylor & Francis e-raamat]

(Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University), ,
  • Formaat: 208 pages
  • Ilmumisaeg: 01-Apr-2003
  • Kirjastus: Psychology Press
  • ISBN-13: 9781410607676
Teised raamatud teemal:
  • Taylor & Francis e-raamat
  • Hind: 161,57 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 230,81 €
  • Säästad 30%
  • Formaat: 208 pages
  • Ilmumisaeg: 01-Apr-2003
  • Kirjastus: Psychology Press
  • ISBN-13: 9781410607676
Teised raamatud teemal:
A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor design).

Providing comprehensive coverage of the basic and advanced topics in ANOVA, this is the only book available that provides extensive coverage of SPSS syntax, including the commands and subcommands that tell SPSS what to do, as well as the pull-down menu point-and-click method (PAC). Detailed explanation of the syntax, including what is necessary, desired, and optional helps ensure that users can validate the analysis being performed. The book features the output of each design along with a complete explanation of the related printout.

The new edition was reorganized to provide all analysis related to one design type in the same chapter. It now features expanded coverage of analysis of covariance (ANCOVA) and mixed designs, new chapters on designs with random factors, multivariate designs, syntax used in PAC, and all new examples of output with complete explanations. The new edition is accompanied by downloadable resources with all of the book's data sets, as well as exercises for each chapter.

This book is ideal for readers familiar with the basic concepts of the ANOVA technique including both practicing researchers and data analysts, as well as advanced students learning analysis of variance.
Preface ix
Table of Topics
xi
Using Spss and Using This Book
1(4)
Conventions for Syntax Programs
1(1)
Creating Syntax Programs in Windows
2(3)
Reading in and Transforming Variables for Analysis in Spss
5(15)
Reading In Data With Syntax
5(4)
Entering Data with the ``DATA LIST'' Command
6(1)
``FREE'' or ``FIXED'' Data Format
7(2)
Syntax for Using External Data
9(1)
Data Entry for SPSS for Windows Users
9(2)
Importing Data
11(1)
Saving and Printing Files
12(1)
Opening Previously Created and Saved Files
12(1)
Output Examination
12(2)
Data Transformations and Case Selection
14(2)
``COMPUTE''
14(1)
``IF''
15(1)
``RECODE''
15(1)
``SELECT IF''
15(1)
Data Transformations with PAC
16(4)
One-Factor Between-Subjects Analysis of Variance
20(22)
Basic Analysis of Variance Commands
20(4)
Testing the Homogeneity of Variance Assumption
24(1)
Comparisons
24(8)
Planned Contrasts
25(3)
Post Hoc Tests
28(4)
Trend Analysis
32(4)
Monotonic Hypotheses
36(1)
PAC
37(5)
Two-Factor Between-Subjects Analysis of Variance
42(17)
Basic Analysis of Variance Commands
42(3)
The Interaction
45(1)
Unequal N Factorial Designs
45(4)
Planned Contrasts and Post Hoc Analyses of Main Effects
49(2)
Exploring a Significant Interaction
51(5)
Simple Effects
51(1)
Simple Comparisons and Simple Post Hocs
52(1)
Interaction Contrasts
53(2)
Trend Interaction Contrasts and Simple Trend Analysis
55(1)
PAC
56(3)
Three (And Greater) Factor Between-Subjects Analysis of Variance
59(8)
Basic Analysis of Variance Commands
59(3)
Exploring a Significant Three-Way Interaction
62(1)
Simple Two-Way Interactions
62(1)
A Nonsignificant Three-Way: Simple Effects
63(3)
Interaction Contrasts, Simple Comparisons, Simple Simple Comparisons, and Simple Interaction Contrasts
64(2)
Collapsing (Ignoring) a Factor
66(1)
More Than Three Factors
66(1)
PAC
66(1)
One-Factor Within-Subjects Analysis of Variance
67(14)
Basic Analysis of Variance Commands
67(3)
Analysis of Variance Summary Tables
70(1)
Correction for Bias in Tests of Within-Subjects Factors
70(2)
Planned Contrasts
72(3)
The ``TRANSFORM/RENAME'' Method for Nonorthogonal Contrasts
73(1)
The ``CONTRAST/WSDESIGN'' Method for Orthogonal Contrasts
74(1)
Post Hoc Tests
75(1)
PAC
75(6)
Two- (Or More) Factor Within-Subjects Analysis of Variance
81(16)
Basic Analysis of Variance Commands
81(3)
Analysis of Variance Summary Tables
84(1)
Main Effect Contrasts
84(4)
Analyzing Orthogonal Main Effects Contrasts (Including Trend Analysis) Using ``CONTRAST/WSDESIGN''
85(1)
Nonorthogonal Main Effects Contrasts Using ``TRANSFORM/RENAME''
86(2)
Simple Effects
88(4)
Analyzing Orthogonal Simple Comparisons Using ``CONTRAST/WSDESIGN''
89(1)
Analyzing Orthogonal Interaction Contrasts Using ``CONTRAST/WSDESIGN''
90(1)
Nonorthogonal Simple Comparisons Using ``TRANSFORM/RENAME''
90(2)
Nonorthogonal Interaction Contrasts Using ``TRANSFORM/RENAME''
92(1)
Post Hocs
92(1)
More Than Two Factors
92(1)
PAC
93(4)
Two-Factor Mixed Designs in Analysis of Variance: One Between-Subjects Factor and One Within-Subjects Factor
97(14)
Basis Analysis of Variance Commands
97(3)
Main Effect Contrasts
100(4)
Between-Subjects Factor(s)
100(1)
Within-Subjects Factor(s)
100(4)
Interaction Contrasts
104(1)
Simple Effects
104(3)
Simple Comparisons
107(2)
Post Hocs and Trend Analysis
109(1)
PAC
109(2)
Three- (Or Greater) Factor Mixed Designs
111(9)
Simple Two-Way Interactions
112(1)
Simple Simple Effects
113(1)
Main Effect Contrasts and Interaction Contrasts
114(2)
Simple Contrasts: Simple Comparisons, Simple Simple Comparisons, and Simple Interaction Contrasts
116(3)
PAC
119(1)
Analysis of Covariance
120(12)
Testing the Homogeneity of Regression Assumption
122(1)
Multiple Covariates
123(1)
Contrasts
124(1)
Post Hocs
124(1)
Multiple Between-Subjects Factors
124(1)
ANCOVAs in Designs With Within-Subjects Factors
125(6)
Constant Covariate
125(2)
Varying Covariate
127(4)
PAC
131(1)
Designs With Random Factors
132(13)
Random Factors Nested in Fixed Factors
133(1)
Subjects as Random Factors in Within-Subjects Designs:
The One-Line-per-Level Setup
134(1)
The One-Factor Within-Subjects Design
134(4)
Two-Factor Mixed Design
138(2)
Using One-Line-per-Level Setup to Get Values to Manually Compute
Adjusted Means in Varying Covariate Within-Subjects ANCOVA
140(3)
PAC
143(2)
Multivariate Analysis of Variance: Designs with Multiple Dependent Variables Tested Simultaneously
145(21)
Basic Analysis of Variance Commands
145(4)
Multivariate Planned Contrasts and Post Hocs
149(1)
Extension to Factorial Between-Subjects Designs
150(1)
Multiple Dependent Variables in Within-Subject Designs:
Doubly Multivariate Designs
150(3)
Contrasts in Doubly Multivariate Designs
153(4)
PAC
157(9)
GLM and Unianova Syntax
166(19)
One-Factor Between-Subjects ANOVA
166(5)
Basic Commands
166(2)
Contrasts
168(3)
Post Hoc Tests
171(1)
Two-Factor Between-Subjects ANOVA
171(6)
Unequal N
171(1)
Main Effects Contrasts and Post Hocs
171(3)
Simple Effects
174(2)
Simple Comparisons
176(1)
Interaction Contrasts
176(1)
Three or More Factor ANOVA
177(1)
One-Factor Within-Subjects ANOVA
177(2)
Basic Commands
177(1)
Planned Contrasts
178(1)
Post Hoc Tests
179(1)
Two or More Factor Within-Subjects ANOVA
179(4)
Main Effect and Interaction Contrasts
180(1)
Simple Effects and Simple Comparisons
181(2)
Mixed Designs
183(2)
More Complex Analyses
183(2)
References 185(1)
Appendix A 186(2)
Appendix B 188(1)
Author Index 189(2)
Subject Index 191
Sanford L. Braver (Author) ,  David P. MacKinnon (Author) ,  Melanie Page (Author)