【基礎編A】構造方程式モデリング入門

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2次因子分析モデル .............................. 111, 112 G A L I B M C D O P E F IBM SPSS Amosによる構造方程式モデリング 184 数字 absolute fit index .............................................. 11 AGFI（Adjusted Goodness of Fit Index） ...... 13 AIC（Akaike Information Criterion） .... 17, 108 BIC（Bayesian Information Criterion） ......... 17 CFI（Comparative Fit of Index） ................... 16 CMIN ............................................................... 12 comparative fit index ........................................ 11 Comparative Fit of Index ................................. 16 configural invariance ...................................... 146 Confirmatory Factor Analysis, CFA ............ 5, 76 Covariance Structure Analysis ........................... 2 degree of freedom ............................................ 10 endogenous variables ......................................... 8 error variables ..................................................... 7 exogenous variables ........................................... 8 Exploratory Factor Analysis, EFA ................... 75 factor ................................................................ 74 factor analysis ................................................... 74 StatsGuild Inc. factor loading ................................................... 77 factorial invariance ......................................... 146 fit index ............................................................ 11 GFI（Goodness of Fit Index） ........................ 13 independence model ......................................... 11 intercept ........................................................... 24 latent variable ..................................................... 7 MIMICモデル ....................................... 111, 112 modification index ................................. 112, 132 multicollinearity ............................................... 59 multi-group analysis ....................................... 144 multiple index model ................................. 6, 110 Multiple Indicator Multiple Cause model ...... 111 multiple population analysis of structural equation modeling ........................................................ 144 observed variable ............................................... 7 parsimony correction index .............................. 11 partial regression coefficient ............................ 25 Path Analysis ............................................... 4, 26 path diagram ...................................................... 2