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Stevens J.P. — Applied multivariate statistics for the social sciences
Stevens J.P. — Applied multivariate statistics for the social sciences



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Название: Applied multivariate statistics for the social sciences

Автор: Stevens J.P.

Аннотация:

A textbook for courses on advanced statistical methods or multivariate statistics for students in the social sciences with little or no training in multivariate methods. Previous study is required in the factorial analysis of variance, but not in matrix algebra. No dates are noted for previous editions. The ISBN on the back cover is different.


Язык: en

Рубрика: Математика/Вероятность/Статистика и приложения/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: fourth edition

Год издания: 2001

Количество страниц: 699

Добавлена в каталог: 10.06.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
A priori ordering, of dependent variables in MANOVA      374
A priori ordering, of predictors in regression analysis      121
Actual alpha      257
Agresti, A.      559 577 596
Ambrose, S.      206
Amlung, S.      420 424
Analysis of covariance (ANCOVA), adjusted means      342
Analysis of covariance (ANCOVA), assumptions      347
Analysis of covariance (ANCOVA), choice of covariates      345
Analysis of covariance, computer example 1 (SAS GLM) — two dependent variables and one covariate      356
Analysis of covariance, computer example 2 (SPSS MANOVA) — 2 dependent variables and 2 covariates      359
Analysis of covariance, computer example 2, homogeneity of regression hyperplanes      355
Analysis of covariance, computer example 2, purposes      340
Analysis of covariance, computer example 2, reduction of error variance      343
Analysis of covariance, computer example 2, use with intact groups      350
Analysis of variance (ANOVA), two way      322—331
Anderson, J.      430
Anderson, N.      324
Anscombe, F.      125
Aptitude treatment interaction      323
Backward selection of predictors      96
Bandalos, D.      433
Barcikowski, R.      260 289 331
Becker, B.      195
Belsey, D.      130 134 135
Beneditti, J.      546
Bentler, P.      429 432 445
Benton, S.      369
Between factor, in repeated measures      493
Big five factors of personality      412
Binomial distribution      561
Bird, K.      218
Bishop, Y.      578 590
Block, J.      412
Bloom's taxonomy      375
Bock, R.      181 244 262 376 382 493
Boik, R.      536
Bollen, K.      414 434 436 427—428 451
Bolton, B.      457
Bonferroni inequality      7
Bonnet, D.      583 586
Boomsma, A.      430
Bootstrapping      468—469
Box test      271
Box, G.      271
Bradley, R.      162
Breckler, S.      452
Brown, M.      149 586
Browne, M.      433
Bryant — Paulson intervals      365
Bryant, J.      362
Bryk, A.      277 351
Byrne, B.      412 445
California Psychological Inventory      396
Canonical correlation, canonical variate-variable correlations      475
Canonical correlation, canonical variates      473
Canonical correlation, computer example (SAS)      476
Canonical correlation, on factor scores      481
Canonical correlation, research applications      472
Canonical correlation, significance tests      473—474
Carlson, J.      331
Carryover effect, in repeated measures      496
Categorical data analysis      see “Loglinear analysis”
Cattell, R.      389
Central limit theorem      262
Church, A.      412
Classification problem      301
Cliff, N.      392 393
Clifford, M.      241
Cochran, W.      340 418 451
Cohen, J.      6 11 82 188 191 194—197 201 226
Collapsibility      see “Loglinear analysis”
Comnmnality issue      409
Confirmatory factor analysis      411
Conover, W.      269
Contrasts, correlated      235
Contrasts, helmert      231—232
Contrasts, independent      227
Contrasts, SPECIAL      232
Cook's distance      126
Cook, R.      126
Cooley, W.      388
Counterbalancing      495
Covariance matrix      62—63
Covariance structural modeling      see “Structural equation modeling”
Covariate by treatment interaction      350
Cramer, E.      484
Crocker, L.      204
Cronbach, L.      1 193 323 336
Cross validation, in discriminant analysis      310
Cross validation, in loglinear analysis      585
Cross validation, in regression analysis      88 115—116
Cross validation, in structural equation modeling      450
Crowder, R.      119
Crystal, G.      81
Daniels, R.      322
Darlington, R.      289 438
DasGupta, S.      245
Data editing      125
Davidson, M.      509
Discriminant analysis, computer example (SPSS)      292
Discriminant analysis, descriptive      285—286
Discriminant analysis, graphing groups      289
Discriminant analysis, interpretation      288
Discriminant analysis, research applications      297
Discriminant analysis, rotation of discriminant functions      296
Discriminant analysis, significance tests      287
Discriminant analysis, stepwise discriminant analysis      296
Distributional tranformations      265
Dizney, H.      92
Draper, N.      82 92 107 127 155
Dummy coding      188
Dunnett, C.      224
Edwards, D.      490
Effect size, multivariate      198
Effect size, univariate      198
Eigenvalues      73
Elashoff, J.      340 350 521
EQS, computer example      445
Error term, for Retelling's      T2
Error term, for t test      178
Everitt, B.      262
Exploratory factor analysis      411
Factor indeterminancy      411
Feshbach, S.      80
Fienberg, S.      570 585 596
Finn, J.      155 354 378
Fisher, R.      302
Forward selection      96
Franc, J.      33
Freeman, D.      590
Friedman, G.      23
General linear model      188
Generalized variance      64
Glasnapp, D.      82
Glass, G.      192 218 222 261
Gnanadesikan, R.      263
Goldberg, L.      412
Golding, S.      455
Goodman, L.      596
Gorsuch, R.      386 410
Green, S.      590
Greenhouse — Geisser epsilon      501
Greenhouse, S.      501
Guadagnoli, R.      395 410
Guttman, L.      88
Haase, R.      11
Haberman, S.      584
Hakstian, R.      270
Harman, H.      410
Harris, R.      180 440
Hat elements      126
Hawkins, D.      297
Hays, W.      191 208 226 228
Helmert      see “Contrasts”
Herzberg, P.      117
Hit rate      304
Hoaglin, D.      130
Hoerl, A.      155
Hogg, R.      125 155
Holland, J.      299
Holloway, L.      270
Homogeneity of hyperplanes      see “ANCOVA”
Hopkins, J.L.      262
Hotelling — Lawley trace      244
Hotelling's T      176
Hotelling, H.      177
Hoyle, R.      449
Huber, P.      125 155
Huberty, C.      97 285 289 301 316
Huck, S.      340 352
Huitema, B.      340 346 348
Hummel, T.      181
Hutchinson, S.      450
Huynh — Feldt estimator      501
Huynh, H.      502
Hykle, J.      258
Idependence of observations, effect on type I error      259
Idependence of observations, what to do with correlated observations      260
Influential data points      126
Interaction, disordinal      322
Interaction, ordinal      322
Intraclass correlation      259
Jackknife      308
Jacobson, R.      12
Jennings, E.      352
Johnson, R.      181 212 263 278 301 316 538
Jorekog, K.      413 415—416 431
Kaiser rule      389
Kaiser, H.      389 391
Keceles      420
Kennedy, J.      559
Kenny, D.      260
Keppel, G.      493
Kerlinger, F.      186 191
KesseIman, H.      502 518
Kirk, R.      191
Kohlberg's theory of moral development      375
Kohlberg, L.      375
Krasker, W.      125
Kvet, E.      512
Lachenbruch, P.      308
Lagrange multiplier      448
Lauter, J.      209 245
Lawley, D.      456
Least squares criterion      82
Levene test      269
Light, R.      10 195
Lindeman, R.      310
Linn, R.      389
LISREL      8
LISREL, computer example      437
Logistic regression      146—153
Loglinear analysis, collapsibility      578
Loglinear analysis, contrasts      590
Loglinear analysis, cross validation      585
Loglinear analysis, for four way tables      586
Loglinear analysis, for three way tables      567
Loglinear analysis, for two way chi square      564
Loglinear analysis, hierarchical models      565
Loglinear analysis, model selection      576
Loglinear analysis, normed fit index      583
Loglinear analysis, odds ratio      582
Loglinear analysis, sampling zeros      596
Loglinear analysis, saturated models      567
Lohnes, P.      212
Lord, F.      93 124
Mahalanobis distance      130
Maiman      420
Mallow's Cp      96
Mallows, C.      96
Marascuilo, L.      590
Mardia, K.      262
Maslach Burnout Inventory      413
Matched pairs, multivariate      512
Matched pairs, univariate      512
Mathematical maximization procedure      88
Matrices, addition      59
Matrices, determinant      64
Matrices, inverse      70
Matrices, multiplication      60—61
Matrices, multiplication by scalar      59
Matrices, SAS IML      76
Matrices, SPSS Matrix      75
Matrices, subtraction      59
Matrices, transpose      57
MAXR procedure      97
Maxwell, S.      352 507 509
McCallum, R.      433 435 450 451
McLean, J.      596
McNeil, K.      297
Measures of association      191
Mendoza, J.      474
Meredith, W.      289
Merenda, P.      472
Milligan, G.      570
Missing data      32—33
Moore, D.      110
Morris, J.      155
Morrison, D.      98 181 246 383 387 390
Mosteller, F.      125 155
Multicollinearity      91—93
Multinomial distribution      561—562
Multiple correlation      88
Multiple regression, caveat on “significance” levels for predictors      107
Multiple regression, checking model assumptions      110—113
Multiple regression, computer example 1, (SPSS) — Morrison MBA data-use of stepwise and backward selection      98—103
Multiple regression, computer example 2, (SAS) — National Academy of Science data-use of stepwise and MAXR      104—107
Multiple regression, controlling order of predictors with SAS and SPSS      121
Multiple regression, importance of order of predictors      119
Multiple regression, mathematical maximization procedure      88
Multiple regression, matrix formulation      86
Multiple regression, model selection      93
Multiple regression, model validation      113—119
Multiple regression, outliers on set of predictors      126
Multiple regression, outliers on y      126
Multiple regression, positive bias of R2      123
Multiple regression, sample size for reliable equation      143
Multiple regression, selection procedures      105
Multivariate analysis of variance (MANOVA), assumptions      257
Multivariate analysis of variance (MANOVA), homogeneity of covariance matri¬ces      269
Multivariate analysis of variance (MANOVA), limiting number of dependent vari¬ables      245
Multivariate analysis of variance (MANOVA), multivariate normality      262
Multivariate analysis of variance (MANOVA), planned comparisons      225
Multivariate analysis of variance (MANOVA), reasons for      225—226
Multivariate analysis of variance (MANOVA), test statistics      228—230
Multivariate regression      155
Myers, J.      278 331 496 516
Myers, R.      82 90 114
Nold, E.      110
Nominal alpha      257
Normal probability plots      264
Normality (univariate), assessing      263
Novince, L.      218 359 379 497
Number of factors problem      389—390
Nunnally, J.      88 401 410 509
O'Brien, R.      509 536
O'Grady, K.      10 191
Oblique rotations      392
Odds ratio      see “Loglinear analysis”
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