Preface |
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xvi | |
Acknowledgments |
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xxi | |
About the Author |
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xxii | |
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Chapter 1 Structural Equation Modeling: The Basics |
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3 | (13) |
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3 | (1) |
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What Is Structural Equation Modeling? |
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3 | (1) |
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4 | (5) |
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Latent versus Observed Variables |
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4 | (1) |
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Exogenous versus Endogenous Latent Variables |
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5 | (1) |
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The Factor Analytic Model |
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5 | (2) |
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The Full Latent Variable Model |
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7 | (1) |
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General Purpose and Process of Statistical Modeling |
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7 | (2) |
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The General Structural Equation Model |
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9 | (6) |
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9 | (1) |
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10 | (1) |
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11 | (1) |
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Nonvisible Components of a Model |
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12 | (1) |
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13 | (1) |
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The Formulation of Covariance and Mean Structures |
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14 | (1) |
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15 | (1) |
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Chapter 2 Using the Amos Program |
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16 | (53) |
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16 | (2) |
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Model Specification Using Amos Graphics (Example 1) |
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18 | (15) |
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19 | (4) |
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23 | (1) |
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23 | (10) |
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Model Specification Using Amos Tables View (Example 1) |
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33 | (10) |
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Understanding the Basic Components of Model 1 |
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40 | (1) |
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The Concept of Model Identification |
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40 | (3) |
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Model Specification Using Amos Graphics (Example 2) |
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43 | (8) |
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43 | (3) |
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46 | (5) |
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Model Specification Using Amos Tables View (Example 2) |
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51 | (2) |
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Model Specification Using Amos Graphics (Example 3) |
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53 | (5) |
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54 | (1) |
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55 | (3) |
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Changing the Amos Default Color for Constructed Models |
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58 | (3) |
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Model Specification Using Amos Tables View (Example 3) |
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61 | (2) |
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63 | (6) |
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Section II Single-Group Analyses |
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Confirmatory Factor Analytic Models |
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Chapter 3 Application 1: Testing the Factorial Validity of a Theoretical Construct (First-Order CFA Model) |
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69 | (46) |
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69 | (1) |
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70 | (1) |
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Hypothesis 1 Self-concept is a 4-Factor Structure |
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70 | (5) |
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Modeling with Amos Graphics |
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75 | (32) |
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75 | (1) |
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75 | (3) |
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78 | (3) |
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Amos Text Output: Hypothesized 4-Factor Model |
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81 | (1) |
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81 | (1) |
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Model Variables and Parameters |
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82 | (1) |
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82 | (2) |
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84 | (2) |
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86 | (16) |
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102 | (5) |
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107 | (1) |
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Hypothesis 2 Self-concept is a 2-Factor Structure |
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108 | (2) |
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Selected Amos Text Output: Hypothesized 2-Factor Model |
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110 | (1) |
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Hypothesis 3 Self-concept is a 1-Factor Structure |
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110 | (1) |
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Modeling with Amos Tables View |
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111 | (2) |
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113 | (2) |
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Chapter 4 Application 2: Testing the Factorial Validity of Scores from a Measurement Scale (First-Order CFA Model) |
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115 | (34) |
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115 | (1) |
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Modeling with Amos Graphics |
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115 | (2) |
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The Measuring Instrument under Study |
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116 | (1) |
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117 | (14) |
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Selected Amos Output: The Hypothesized Model |
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119 | (7) |
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126 | (5) |
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131 | (1) |
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132 | (4) |
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Selected Amos Output: Model 2 |
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132 | (4) |
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136 | (3) |
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Selected Amos Output: Model 3 |
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136 | (3) |
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139 | (7) |
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Selected Amos Output: Model 4 |
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139 | (6) |
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Comparison with Robust Analyses Based on the Satorra--Bentler Scaled Statistic |
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145 | (1) |
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Modeling with Amos Tables View |
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146 | (2) |
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148 | (1) |
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Chapter 5 Application 3: Testing the Factorial Validity of Scores from a Measurement Scale (Second-Order CFA Model) |
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149 | (36) |
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149 | (1) |
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150 | (2) |
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Modeling with Amos Graphics |
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152 | (11) |
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Selected Amos Output File: Preliminary Model |
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155 | (6) |
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Selected Amos Output: The Hypothesized Model |
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161 | (1) |
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161 | (2) |
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Estimation Based on Continous Versus Categorical Data |
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163 | (7) |
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Categorical Variables Analyzed as Continuous Variables |
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167 | (1) |
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Categorical Variables Analyzed as Categorical Variables |
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168 | (2) |
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The Amos Approach to Analysis of Categorical Variables |
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170 | (10) |
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What is Bayesian Estimation? |
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171 | (1) |
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Application of Bayesian Estimation |
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171 | (9) |
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Modeling with Amos Tables View |
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180 | (2) |
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182 | (3) |
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Full Latent Variable Model |
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Chapter 6 Application 4: Testing the Validity of a Causal Structure |
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185 | (42) |
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185 | (1) |
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186 | (1) |
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Modeling with Amos Graphics |
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187 | (16) |
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Formulation of Indicator Variables |
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187 | (2) |
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Confirmatory Factor Analyses |
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189 | (8) |
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Selected Amos Output: Hypothesized Model |
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197 | (2) |
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199 | (4) |
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203 | (16) |
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Selected Amos Output: Model 2 |
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203 | (1) |
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203 | (1) |
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Selected Amos Output: Model 3 |
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204 | (1) |
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204 | (1) |
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Selected Amos Output: Model 4 |
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205 | (1) |
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205 | (1) |
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Selected Amos Output: Model 5 |
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206 | (1) |
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206 | (2) |
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Selected Amos Output: Model 6 |
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208 | (1) |
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208 | (1) |
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The Issue of Model Parsimony |
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208 | (2) |
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Selected Amos Output: Model 7 (Final Model) |
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210 | (1) |
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210 | (2) |
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212 | (7) |
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Modeling with Amos Tables View |
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219 | (2) |
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221 | (6) |
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Section III Multiple-Group Analyses |
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Confirmatory Factor Analytic Models |
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Chapter 7 Application 5: Testing Factorial Invariance of Scales from a Measurement Scale (First-Order CFA Model) |
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227 | (36) |
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227 | (2) |
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Testing For Multigroup Invariance |
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229 | (1) |
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229 | (1) |
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230 | (1) |
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230 | (5) |
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Establishing Baseline Models: The General Notion |
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231 | (1) |
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Establishing the Baseline Models: Elementary and Secondary Teachers |
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231 | (4) |
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Modeling with Amos Graphics |
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235 | (3) |
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Hierarchy of Steps in Testing Multigroup Invariance |
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238 | (23) |
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I Testing for Configural Invariance |
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238 | (2) |
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Selected Amos Output: The Configural Model (No Equality Constraints Imposed) |
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240 | (4) |
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II Testing for Measurement and Structural Invariance: The Specification Process |
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244 | (8) |
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III Testing for Measurement and Structural Invariance: Model Assessment |
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252 | (1) |
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Testing For Multigroup Invariance: The Measurement Model |
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253 | (1) |
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253 | (8) |
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Testing For Multigroup Invariance: The Structural Model |
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261 | (1) |
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261 | (2) |
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Chapter 8 Application 6: Testing Invariance of Latent Mean Structures (First-Order CFA Model) |
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263 | (30) |
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263 | (1) |
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Basic Concepts Underlying Tests of Latent Mean Structures |
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264 | (3) |
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Estimation of Latent Variable Means |
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266 | (1) |
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267 | (2) |
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269 | (1) |
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Modeling with Amos Graphics |
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269 | (2) |
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The Structured Means Model |
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269 | (2) |
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Testing for Latent Mean Differences |
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271 | (18) |
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The Hypothesized Multigroup Model |
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271 | (1) |
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Steps in the Testing Process |
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271 | (8) |
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Selected Amos Output: Model Summary |
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279 | (2) |
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Selected Amos Output: Goodness-of-fit Statistics |
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281 | (2) |
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Selected Amos Output: Parameter Estimates |
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283 | (6) |
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289 | (4) |
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Full Latent Variable Model |
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Chapter 9 Application 7: Testing Invariance of a Causal Structure (Full Structural Equation Model) |
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293 | (18) |
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293 | (1) |
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Cross-Validation in Covariance Structure Modeling |
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293 | (3) |
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Testing for Invariance across Calibration/Validation Samples |
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296 | (1) |
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296 | (7) |
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Establishing a Baseline Model |
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298 | (5) |
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Modeling with Amos Graphics |
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303 | (8) |
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Testing for the Invariance of Causal Structure Using the Automated Multigroup Approach |
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303 | (2) |
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Selected Amos Output: Goodness-of-fit Statistics for Comparative Tests of Multigroup Invariance |
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305 | (6) |
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Section IV Other Important Applications |
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Chapter 10 Application 8: Testing Evidence of Construct Validity: The Multitrait-Multimethod Model |
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311 | (28) |
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311 | (2) |
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The Correlated Traits-Correlated Methods Approach to MTMM Analyses |
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313 | (14) |
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Model 1 Correlated Traits-Correlated Methods |
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315 | (5) |
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Model 2 No Traits-Correlated Methods |
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320 | (2) |
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Model 3 Perfectly Correlated Traits-Freely Correlated Methods |
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322 | (4) |
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Model 4 Freely Correlated Traits-Uncorrelated Methods |
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326 | (1) |
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Testing for Evidence of Convergent and Discriminant Validity: MTMM Matrix-level Analyses |
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327 | (1) |
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327 | (1) |
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Evidence of Convergent Validity |
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327 | (1) |
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Evidence of Discriminant Validity |
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327 | (1) |
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Testing for Evidence of Convergent and Discriminant Validity: MTMM Parameter-level Analyses |
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328 | (3) |
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Examination of Parameters |
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328 | (1) |
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Evidence of Convergent Validity |
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329 | (2) |
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Evidence of Discriminant Validity |
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331 | (1) |
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The Correlated Uniquenesses Approach to MTMM Analyses |
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331 | (7) |
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Model 5 Correlated Uniqueness Model |
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335 | (3) |
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338 | (1) |
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Chapter 11 Application 9: Testing Change Over Time: The Latent Growth Curve Model |
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339 | (26) |
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339 | (2) |
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Measuring Change in Individual Growth over Time: The General Notion |
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341 | (1) |
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The Hypothesized Dual-domain LGC Model |
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341 | (5) |
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Modeling Intraindividual Change |
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341 | (4) |
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Modeling Interindividual Differences in Change |
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345 | (1) |
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Testing Latent Growth Curve Models: A Dual-Domain Model |
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346 | (8) |
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346 | (4) |
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Selected Amos Output: Hypothesized Model |
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350 | (4) |
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Testing Latent Growth Curve Models: Gender as a Time-invariant Predictor of Change |
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354 | (7) |
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361 | (4) |
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Section V Other Important Topics |
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Chapter 12 Application 10: Use of Bootstrapping in Addressing Nonnormal Data |
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365 | (28) |
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365 | (3) |
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Basic Principles Underlying the Bootstrap Procedure |
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368 | (2) |
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Benefits and Limitations of the Bootstrap Procedure |
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369 | (1) |
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Caveats Regarding the Use of Bootstrapping in SEM |
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369 | (1) |
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Modeling with Amos Graphics |
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370 | (5) |
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371 | (1) |
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Characteristics of the Sample |
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371 | (2) |
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Applying the Bootstrap Procedure |
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373 | (2) |
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375 | (17) |
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375 | (1) |
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376 | (2) |
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Parameter Estimates and Standard Errors |
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378 | (14) |
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392 | (1) |
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Chapter 13 Application 11: Addressing the Issues of Missing Data |
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393 | (14) |
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393 | (1) |
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Basic Patterns of Missing Data |
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394 | (2) |
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Common Approaches to Handling Incomplete Data |
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396 | (4) |
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Ad Hoc Approaches to Handling Missing Data (Not recommended) |
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396 | (3) |
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Theory-based Approaches to Handling Missing Data (Recommended) |
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399 | (1) |
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The Amos Approach to Handling Missing Data |
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400 | (1) |
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Modeling with Amos Graphics |
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401 | (5) |
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401 | (3) |
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Selected Amos Output: Parameter and Model Summary Information |
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404 | (1) |
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Selected Amos Output: Parameter Estimates |
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405 | (1) |
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Selected Amos Output: Goodness-of-fit Statistics |
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406 | (1) |
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406 | (1) |
References |
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407 | (21) |
Author Index |
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428 | (5) |
Subject Index |
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433 | |