SPSS see "Statistical Package for the Social Sciences (SPSS)"
Square-root transformation 383
Squared multiple correlation, computation of 181
Squared multiple correlation, LISREL 163—164
Standard basis vectors 25
Standard normal probabilities, table of 457
Standardization of data 39
Standardization of data, correlation coefficient 39
Standardization of data, Euclidian distance for standardized data 219
Standardization of data, graphical representations in space 47—50
Standardized canonical discriminant function 253—254
Statistical Analysis System (SAS), canonical correlation 398—406
Statistical Analysis System (SAS), chi-square plot 389—390
Statistical Analysis System (SAS), cluster analysis, hierarchical 193—202
Statistical Analysis System (SAS), cluster analysis, nonhierarchical 207—210
Statistical Analysis System (SAS), data manipulations 55—57
Statistical Analysis System (SAS), factor analysis 109—115
Statistical Analysis System (SAS), logistic regression 321—335
Statistical Analysis System (SAS), maximum likelihood estimation technique 148
Statistical Analysis System (SAS), measurement models estimation 14
Statistical Analysis System (SAS), ordinary least squares estimation 421
Statistical Analysis System (SAS), principal components analysis 67-71
Statistical Analysis System (SAS), structural model estimation 426
Statistical decision theory 256—257
Statistical decision theory, classification rules, development of 279—281
Statistical distance 42—44
Statistical distance and Euclidian distance 43—44
Statistical distance, squared statistical distance 43
Statistical Package for the Social Sciences (SPSS) 67
Statistical Package for the Social Sciences (SPSS), classification 256—257 261
Statistical Package for the Social Sciences (SPSS), confirmatory factor analysis, LISREL 148—177
Statistical Package for the Social Sciences (SPSS), discriminant analysis 245—262
Statistical Package for the Social Sciences (SPSS), Helmert contrasts 360—361
Statistical Package for the Social Sciences (SPSS), MANOVA, for two independent variables 366—371
Statistical Package for the Social Sciences (SPSS), MANOVA, multiple group 355—366
Statistical Package for the Social Sciences (SPSS), MANOVA, two-group 350—355
Statistical Package for the Social Sciences (SPSS), measurement models estimation 14
Statistical Package for the Social Sciences (SPSS), multiple-group discriminant analysis 294—308
Statistical Package for the Social Sciences (SPSS), orthogonal contrasts 360—363
Statistical Package for the Social Sciences (SPSS), stepwise discriminant analysis 267—273
Statistical Package for the Social Sciences (SPSS), univariate normality 378—379
Statistical significance of discriminant function 252—253 299—302
Statistical significance, structural models 430 439
Statistical significance, tests for canonical correlations 402—404
Statistical tables,  critical points 459
Statistical tables, F-distribution 460—465
Statistical tables, percent points of normal probability plot correlation coefficient 466
Statistical tables, simulation percentiles of  467
Statistical tables, simulation probability points of  467
Statistical tables, standard normal probabilities 457
Statistical tables, student's t-distribution critical points 458
Statistical tests, multivariate normality tests 380—383
Statistical tests, power of test 375
Statistical tests, Type I and Type II errors 374—375
Statistical tests, univariate normality tests 375—380
Stepwise discriminant analysis 264—273
Stepwise discriminant analysis and multicollinearity 272—273
Stepwise discriminant analysis, backward selection 265
Stepwise discriminant analysis, computer analysis 267—273
Stepwise discriminant analysis, cutoff values for selection criteria 266—267
Stepwise discriminant analysis, F-ratio in 266 271
Stepwise discriminant analysis, forward selection 265
Stepwise discriminant analysis, Mahalanobis squared distance in 266
Stepwise discriminant analysis, Ray's V in 266
Stepwise discriminant analysis, selection criteria 265—266
Stepwise discriminant analysis, stepwise selection 265
Stepwise discriminant analysis, Wilks'A test statistic in 251 266
Stepwise selection procedure, in logistic regression 329 331—332
Structural correlations 404
Structural models 13—14 435—437
Structural models and implied covariance matrix 444—449
Structural models and latent constructs 13 14
Structural models with observable constructs 420—426 444—446
Structural models with unobservable constructs 426—435 446—449
Structural models, assessment of 438—439
Structural models, direct effects 425 450 452
Structural models, effects among constructs 430
Structural models, effects among endogenous constructs 450—452
Structural models, effects of constructs on its indicators 452—453
Structural models, effects of endogenous constructs on indicators 434
Structural models, effects of exogenous constructs on endogenous constructs 45
Structural models, effects of exogenous constructs on indicators 430
Structural models, effects of exogenous constructs on indicators of endogenous constructs 435
Structural models, estimation procedures in computer packages 14
Structural models, examples of use 13 435—439
Structural models, indirect effects 425 450—451 452—453
Structural models, LISREL estimation 421—434
Structural models, measurement model, assessment of 437
Structural models, model fit, assessment of 435—437
Structural models, model respecification 435—437
Structural models, overall model fit 425
Structural models, saturated models 421
Structural models, standardized solution 426 435
Structural models, statistical significance 430 439
Structural models, structural equations 419—420
Structural models, t-values 425
Structural models, total coefficient of determination for 424
Structural models, total effects 425 451
Structure coefficients 254
Structure loading 92
Student's r-distribution critical points, table of 458
Sum of cross products 39
Sum of cross products, computation of 39
Sum of cross products, sum of squares and cross products matrix 39
Sum of squares 38—39
Sum of squares and cross products matrix 39
Sum of squares and cross products matrix and between-group analysis 42
| Sum of squares and cross products matrix and within-group analysis 40—41
Sum of squares for correlated contrasts 365—366
Summary measures, computer procedures for 55—57
Summary measures, data manipulations for 36—42
Summary measures, types of 36
Symmetry, and Mahalonobis distance 45
T-test, in discriminant analysis 244—245 246 250
T-values, in structural model 425
Territorial map, purpose of 303
Tied pairs 325—326
Total coefficient of determination for structural equations 424
Total coefficient of determination, LISREL 164
Transformation, Fisher's Z transformation 383
Transformation, logit transformation 383
Transformation, multivariate normality test 383
Transformation, square-root transformation 383
Triangular inequality, and Mahalonobis distance 45
Tucker — Lewis index 160
Two-factor model with correlated constructs 147
Two-factor model with LISREL 165—170
Two-factor model, computation of 133—135
Two-factor model, situations for use 93—96
Two-group discriminant analysis and classification 242—244 278—284
Two-group discriminant analysis, analytical approach to 244—245
Two-group discriminant analysis, compared to principal components analysis 241—242
Two-group discriminant analysis, computer analysis 245—262
Two-group discriminant analysis, discriminant function 242 250—254
Two-group discriminant analysis, discriminating variables, evaluation of significance 246 250
Two-group discriminant analysis, discriminator variables, selection of 244-245
Two-group discriminant analysis, equality of covariance matrices 264
Two-group discriminant analysis, Fisher's linear discriminant function 245 277—278
Two-group discriminant analysis, geometric view of 237—244
Two-group discriminant analysis, identification of set of variables 238
Two-group discriminant analysis, multiple regression approach to 262—263
Two-group discriminant analysis, multivariate normality assumption 263-264
Two-group discriminant analysis, new axis, identification of 239—242
Two-group discriminant analysis, objectives of 237 241 242
Two-group discriminant analysis, stepwise discriminant analysis 246 264—273
Two-group discriminant analysis, validation of discriminant function 273—274
Two-group MANOVA 350—355
Two-group MANOVA, cell means 351
Two-group MANOVA, computer analysis 350—355
Two-group MANOVA, homogeneity of variances 351
Two-group MANOVA, multivariate significance tests and power 351 353
Two-group MANOVA, univariate significance tests and power 353—355
Two-stage least-squares approach, in LISREL 152
Type I errors and violation of equality of covariance matrices 384
Type I errors, nature of 374
Type II errors, nature of 375
U-method, discriminant function validation 273—274
Unconstrained analysis, LISREL 171
Univariate analysis, number of variables 5
Univariate analysis, objectives of 238
Univariate effect size 349
Univariate normal distribution, kurtosis, of 375
Univariate normal distribution, zero skewness of 375
Univariate normality tests 375—380
Univariate normality tests, analytical procedures 378
Univariate normality tests, computer analysis 378—379
Univariate normality tests, graphical tests 376—377
Univariate significance tests 250
Univariate significance tests for contrasts 357—359 360 362—363
Univariate significance tests in multivariate analysis of variance (MANOVA) 348—349
Univariate significance tests, two-group MANOVA 353
Unobservable construct 91
Validity of canonical coefficients 409
Validity, cluster analysis 221
Variable space, graphical representation of data in 45—46
Variables, number for measurement scales 3—4
Variance of standardized variables 39
Variance, computation of 38
Variance, generalized variance 39 50—51 54—55
Variance, situations for use 38
Varimax factor rotation 119—120 138
Vectors 19—32
Vectors in Cartesian coordinate system 23—25
Vectors, addition of 21—22
Vectors, arithmetic operations on 25—26
Vectors, basis vectors 25 31
Vectors, centroid 45—46
Vectors, changing basis 31—32
Vectors, dimensionality of 30—31
Vectors, distance and angle between two vectors 27
Vectors, equivalent vectors 20
Vectors, initial and terminal point 19
Vectors, linear combination of 26—27
Vectors, multiplication by real number 20—21
Vectors, multiplication of two vectors 22—23
Vectors, norm of 20
Vectors, null vector 21
Vectors, oblique basis 31
Vectors, orthonormal vectors 25 31 32
Vectors, projection into subspace 28—29
Vectors, projection of one onto another 23
Vectors, projection vector 23 27—28
Vectors, reflection 21
Vectors, representation of points with respect to new axes 32—33
Vectors, scalar product of two vectors 20—21 27—28
Vectors, signed length of 28
Vectors, standard basis vectors 25
Vectors, subtraction of 22
Ward's method, hierarchical clustering method 193 217
Wilks'A test statistic in discriminant analysis 246—250
Wilks'A test statistic in stepwise discriminant analysis 251 266
Wilks'A test statistic, relationship to F-ratio 348
Wilks'A test statistic, testing for canonical correlations 402—403
Within-group analysis 40—41
Within-group analysis, sum of squares and cross products matrices 40—41
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