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