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Basic Definitions and Overview |
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1 | (24) |
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4 | (2) |
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6 | (8) |
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6 | (1) |
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Between-Dyads, Within-Dyads, and Mixed Variables |
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7 | (2) |
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9 | (1) |
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Idiographic and Nomothetic Analyses |
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10 | (1) |
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11 | (3) |
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14 | (6) |
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14 | (5) |
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19 | (1) |
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A Database of Dyadic Studies |
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20 | (1) |
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21 | (2) |
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23 | (2) |
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The Measurement of Nonindependence |
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25 | (28) |
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Interval Level of Measurement |
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27 | (13) |
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27 | (5) |
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Indistinguishable Members |
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32 | (8) |
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40 | (3) |
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40 | (2) |
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Indistinguishable Members |
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42 | (1) |
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Consequences of Ignoring Nonindependence |
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43 | (3) |
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46 | (2) |
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48 | (3) |
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48 | (2) |
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50 | (1) |
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51 | (2) |
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Analyzing Between- and Within-Dyads Independent Variables |
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53 | (25) |
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Interval Outcome Measures and Categorical Independent Variables |
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54 | (16) |
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One Between-Dyads Independent Variable |
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54 | (6) |
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Multiple Between-Dyads Independent Variables |
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60 | (1) |
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One Within-Dyads Independent Variable |
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61 | (4) |
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Multiple Within-Dyads Variables |
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65 | (2) |
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One Between-Dyads and One Within-Dyads Variable |
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67 | (2) |
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69 | (1) |
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Interval Outcome Measures and Interval Independent Variables |
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70 | (4) |
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Between-Dyads Independent Variable |
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70 | (2) |
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Within-Dyads Independent Variable |
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72 | (2) |
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74 | (1) |
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Categorical Outcome Variables |
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74 | (1) |
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Within-Dyads Independent Variable |
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74 | (1) |
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Between-Dyads Independent Variable |
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75 | (1) |
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75 | (3) |
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Using Multilevel Modeling to Study Dyads |
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78 | (22) |
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79 | (3) |
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Multilevel-Model Equations |
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82 | (3) |
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Multilevel Modeling with Maximum Likelihood |
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85 | (2) |
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Adaptation of Multilevel Models to Dyadic Data |
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87 | (11) |
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Computing the Intraclass Correlation and Variance Explained with Multilevel Models |
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93 | (2) |
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Random Effects with Dyads |
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95 | (1) |
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95 | (3) |
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98 | (2) |
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Using Structural Equation Modeling to Study Dyads |
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100 | (19) |
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101 | (5) |
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101 | (1) |
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102 | (1) |
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103 | (1) |
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104 | (2) |
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Confirmatory Factor Analysis |
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106 | (2) |
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Path Analyses with Dyadic Data |
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108 | (3) |
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SEM for Dyads with Indistinguishable Members |
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111 | (5) |
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Model Fit and Model Comparisons |
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113 | (1) |
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114 | (2) |
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116 | (1) |
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116 | (3) |
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Tests of Correlational Structure and Differential Variance |
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119 | (25) |
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121 | (14) |
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121 | (1) |
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122 | (5) |
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Latent-Variable Correlations |
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127 | (2) |
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Omnibus Test of Distinguishability |
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129 | (2) |
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131 | (4) |
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135 | (6) |
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136 | (3) |
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Latent Variable Correlations |
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139 | (1) |
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Comparing Intraclass Correlations |
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140 | (1) |
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141 | (1) |
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141 | (3) |
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Analyzing Mixed Independent Variables: The Actor-Partner Interdependence Model |
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144 | (41) |
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145 | (2) |
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Conceptual Interpretation of Actor and Partner Effects |
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147 | (5) |
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The Relative Size of Actor and Partner Effects |
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147 | (2) |
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Partner-Oriented Interaction Effects |
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149 | (1) |
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Actor-Partner Interactions |
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150 | (2) |
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Estimation of the APIM: Indistinguishable Dyad Members |
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152 | (18) |
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152 | (6) |
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Estimating the APIM with Multilevel Analysis |
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158 | (10) |
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Estimating the APIM with SEM |
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168 | (2) |
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Estimation of the APIM: Distinguishable Dyads |
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170 | (9) |
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170 | (3) |
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173 | (5) |
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Structural Equation Modeling |
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178 | (1) |
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Power and Effect Size Computation |
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179 | (2) |
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Specification Error in the APIM |
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181 | (1) |
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182 | (3) |
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Social Relations Designs with Indistinguishable Members |
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185 | (38) |
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The Basic Data Structures |
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188 | (3) |
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188 | (1) |
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189 | (1) |
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Block-Round-Robin Designs |
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190 | (1) |
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190 | (1) |
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191 | (20) |
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191 | (3) |
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Estimation of SRM Effects |
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194 | (4) |
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198 | (6) |
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The SRM Reciprocity Correlations |
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204 | (4) |
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Self-Actor and Self-Partner Correlations |
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208 | (1) |
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Actor and Partner Correlations with Individual-Difference Variables |
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209 | (1) |
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Dyadic Analysis of Relationship Effects |
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210 | (1) |
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Multivariate Correlations |
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210 | (1) |
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Details of an SRM Analysis |
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211 | (4) |
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211 | (1) |
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212 | (1) |
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213 | (1) |
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214 | (1) |
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215 | (3) |
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Social Relations Analyses: An Example |
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218 | (3) |
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221 | (2) |
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Social Relations Designs with Roles |
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223 | (40) |
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SRM Studies of Family Relationships |
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224 | (1) |
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Design and Analysis of Studies |
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225 | (1) |
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226 | (5) |
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227 | (1) |
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Generalized and Dyadic Reciprocity |
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228 | (1) |
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Estimation of Variance in the SRM with Roles |
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228 | (1) |
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229 | (2) |
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Application of the SRM with Roles Using Confirmatory Factor Analysis |
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231 | (3) |
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234 | (5) |
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235 | (4) |
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Illustration of the Four-Person Family Design |
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239 | (6) |
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240 | (1) |
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240 | (3) |
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Respecifications of the Base Model |
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243 | (2) |
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245 | (7) |
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245 | (3) |
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248 | (2) |
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Alternative Three-Person Models |
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250 | (2) |
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Multiple Perspectives on Family Relationships |
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252 | (1) |
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Means and Factor Score Estimation |
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253 | (6) |
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Constraints on the SRM Effects |
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257 | (1) |
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Estimation of SRM Effects for a Particular Family |
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258 | (1) |
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259 | (1) |
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260 | (3) |
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263 | (33) |
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264 | (3) |
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Measuring Nonindependence |
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267 | (4) |
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Indistinguishable Partners |
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267 | (2) |
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269 | (2) |
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The Meaning of Nonindependence in the One-with-Many Design |
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271 | (1) |
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Univariate Analysis with Indistinguishable Partners |
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272 | (12) |
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273 | (2) |
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275 | (2) |
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277 | (7) |
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Univariate Estimation with Distinguishable Partners |
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284 | (6) |
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Repeated-Measures Analysis of Variance and MANOVA |
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284 | (1) |
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285 | (2) |
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Structural Equation Modeling |
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287 | (3) |
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The Reciprocal One-with-Many Design |
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290 | (4) |
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Indistinguishable Partners |
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290 | (3) |
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293 | (1) |
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294 | (2) |
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296 | (21) |
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296 | (2) |
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The Representation of a Network |
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298 | (3) |
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301 | (8) |
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301 | (3) |
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304 | (1) |
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305 | (1) |
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306 | (3) |
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309 | (1) |
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309 | (5) |
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309 | (4) |
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313 | (1) |
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Another Look at the Sampson Data |
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314 | (1) |
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314 | (3) |
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317 | (25) |
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319 | (2) |
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Measures of Profile Similarity |
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321 | (6) |
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321 | (4) |
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325 | (2) |
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Mean and Variance of the Dyadic Index |
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327 | (3) |
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327 | (1) |
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328 | (2) |
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330 | (4) |
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Differential Endorsement of the Stereotype |
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334 | (1) |
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335 | (2) |
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Idiographic versus Nomothetic Analysis |
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337 | (1) |
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338 | (2) |
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340 | (2) |
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Over-Time Analyses: Interval Outcomes |
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342 | (39) |
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344 | (12) |
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347 | (1) |
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348 | (3) |
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351 | (5) |
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356 | (3) |
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Specification of Error Structure |
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357 | (1) |
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Measurement of the Causal Variable |
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358 | (1) |
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358 | (1) |
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359 | (11) |
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360 | (1) |
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360 | (3) |
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Structural Equation Modeling |
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363 | (4) |
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367 | (1) |
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368 | (1) |
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369 | (1) |
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370 | (6) |
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Nonlinear Dynamic Modeling |
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376 | (2) |
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378 | (3) |
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Over-Time Analyses: Dichotomous Outcomes |
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381 | (25) |
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383 | (5) |
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384 | (2) |
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386 | (2) |
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Statistical Analysis of Sequential Data: Log-Linear Analysis |
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388 | (8) |
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389 | (3) |
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Significance Testing and Aggregation across Dyads |
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392 | (2) |
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The Assumption of Stationarity in Time-Series Analysis |
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394 | (1) |
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Beyond the Basic Analysis |
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395 | (1) |
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Statistical Analysis of Sequential Data: Multilevel Modeling |
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396 | (3) |
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399 | (5) |
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401 | (2) |
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403 | (1) |
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403 | (1) |
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404 | (2) |
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406 | (21) |
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Specialized Dyadic Models |
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406 | (7) |
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406 | (3) |
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409 | (4) |
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413 | (3) |
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413 | (1) |
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414 | (1) |
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414 | (2) |
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Conceptual and Practical Issues |
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416 | (5) |
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The Meaning of Nonindependence |
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416 | (4) |
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Design and Measurement Issues in Dyadic Research |
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420 | (1) |
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Recruitment and Retention |
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421 | (1) |
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The Seven Deadly Sins of Dyadic Data Analysis |
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421 | (3) |
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424 | (3) |
References |
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427 | (18) |
Index |
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445 | |