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Harris R.J. — A primer of multivariate statistic

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Название: A primer of multivariate statistic

Автор: Harris R.J.

Аннотация:

As he was looking over materials for his multivariate course, Harris (U. of New Mexico) realized that the course had outstripped the current edition of his own textbook. He decided to revise it rather than use someone else's because he finds them veering too much toward math avoidance, and not paying enough attention to emergent variables or to structural equation modeling. He has updated the 1997 second edition with new coverage of structural equation modeling and various aspects of it, new demonstrations of the properties of the various techniques, and computer applications integrated into each chapter rather than appended.

Язык:

Рубрика: Математика/Вероятность/Статистика и приложения/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: third edition

Год издания: 2001

Количество страниц: 609

Добавлена в каталог: 03.06.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID

Предметный указатель

as z-score regression coefficients      77t 83 84t 85—91
      See Degrees of freedom
analysis      184 231
      See Hotelling's $T^2$

$\alpha$ (alpha)      See Error rate; Type I error
$\beta$ (beta) values, as population regression coefficients      60—113
$\rho$ (rho)      See Spearman's rho
$\tau$       See Kendall's tau
$\varepsilon$ (epsilon) as measure of departure from h.o.t.d.v.      191
A priori, division of alpha      13
A priori, factor structure      43 407
A priori, significance criteria      80 94 156 157 160—161 168 172 181 190—191 214 222t 223 238 246 263
A, as cross-product matrix      160 170
Absolute values, use of      158
Accuracy criterion      541
Adams' ratio formula      156 162 164—165
Adams, J.S.      156 162 164—165
Additive partition      See Partitioning additive
Adjective scales      26
Aggression      44
Akey, T.M.      0
Algebraic forms      See Matrix algebra
Allocation problems      156 162
AMOS program      433 478
Anagrams      114 155 157n 188
Analysis of covariance (Ancova)      15 38—40
Analysis of covariance (Ancova), in repeated-measures design      39—40
Analysis of covariance (Ancova), multivariate      16t 39
Analysis of covariance (Ancova), via regression analysis      38
Analysis of variance (Anova)      11n
Analysis of variance (Anova), as effects model of      111
Analysis of variance (Anova), basic procedures of      210—213
Analysis of variance (Anova), Bonferroni-adjusted comparisons in      213 215—218
Analysis of variance (Anova), error terms      185 220 245 252 260 263 265 266
Analysis of variance (Anova), F ratio      4 20—21 191
Analysis of variance (Anova), factorial model      11n 113 243—244
Analysis of variance (Anova), grand mean in      114
Analysis of variance (Anova), higher order      16t 18 26—27 243—244
Analysis of variance (Anova), interaction terms of      32 243—245
Analysis of variance (Anova), Kruskal — Wallis      451
Analysis of variance (Anova), least squares versus unweighted means      113—114 545
Analysis of variance (Anova), matrix operations in      17
Analysis of variance (Anova), means model and      111
Analysis of variance (Anova), MRA and      111—121 544
Analysis of variance (Anova), on change scores      39
Analysis of variance (Anova), on discriminant function      251—252 251t
Analysis of variance (Anova), one-way      18—21 210—219 557
Analysis of variance (Anova), profile analysis and      175
Analysis of variance (Anova), repeated-measures and      22 188—189 189t 190—191
Analysis of variance (Anova), Scheffe's contrast method and      32 213—215 215t 221—222 222t
Analysis of variance (Anova), sources of variance      245 248t 25
Analysis of variance (Anova), summary table for      213t
Analysis of variance (Anova), unequal ns, alternative analyses      116—121
Analysis of variance (Anova), univariate analysis      11n 10 36 210—215 215t 221 224 248t 252—257
Analysis of variance (Anova), unweighted means      545
Analysis of variance (Anova), within-subject analysis      189—191 199 252—257
Ancova      See Analysis of covariance
Anderson, N.H.      0
Anderson, T.W      30n 353 479
anova      See Analysis of variance
Anscombe, F.J.      1 3 76
Antimasculinism      446
Anxiety      13 22 39
APA Task Force on Statistical Inference      0
Apology game      282
Appelbaum, M.I.      190
Arbuckle, J.L.      478
Architecture, and factor analysis      373—378 374 375t 377
Arcsin transformation of proportions      480
Association, measures of      36 294 295
Assumptions, distributional      445
Assumptions, equal covariance matrices      185—187 232 237
Assumptions, homogeneity of main-diagonal submatrices      284
Assumptions, homogeneity of treatment-difference variances      190
Assumptions, homogeneity of variance      212
Assumptions, of multivariate normality      76 187 231—232 236 450—453
Astrology, value of      55
Atkinson, R.C.      5 78
Attention measures      87
Attitude scale      106 326
Attitudes survey      326 343—344 344t
Authoritarianism, measures of      36
Avery, S.E.      191
Axes, rotation of      358 358—360
b coefficient, as sample regression coefficients      62—121
b coefficient, principal components and      41 236—243
Background variables      2 21 33 34 55 56 206 274 275t 276t
Background, noisy      3 8
Bailey, D.E.      409 480
Baker, R.      33
Bales' interaction process analysis      36
Bartlett's chi-square approximation to distribution of U-statistic      234
Bartlett's test of homogeneity of variance      186 452
Bartlett, M.S.      106 234—236 355 452
Baseline scores      40
Basis submatrix      460
Battle of Sexes game      282—283 283t
Baumert, J.      480
Bayesian statistics      2—3
Bednarz, J.      201
Beefy-breasted Bowery birds (BBBBs)      290—293 291t
Behavior, consistency of individual differences in      282—284
Behavior, in games      336
Behavior, mathematical models of      5—6 63
Behavior, motives and      25
Behrens — Fisher tests      187
Bentler, P.M.      6 473 479
Best Linear Unbiased Estimators (BLUE)      122
Between-condition differences      180
Between-group mean square      19
Between-set relationships      36
Between-subjects effects      27 253
Bias, in estimators      122 295—296
Billings, D.K.      273
Binary prediction      1
Bird, K.      233—234 237—238 244 347—348 414 452
Biserial correlation      30 445—446
Bishop, Y.M.M.      480
Bivariate regression      15 28—31 559
Black box approach      51
Blocking factor      39
Blood doping      192—196
blue      See Best Linear Unbiased Estimators
BMD programs      106 145
BMD02R program      106 145
BMDX69 program      19 249—250
BMDX69 program, BMDP programs      98
Bochner, S.      28 113—114 345 345t
Bock, R.D.      233 480
Bohnenblust, V.      57
Boik, R.J.      191 245 252
Boldface notation      489
Bolton, B.      394
Boneau, C.A.      450
Bonferroni adjustments      13—14 21 24 45 54 164 187 191—192 213 215—218
Bonferroni adjustments, CIs and      81
Bonferroni adjustments, disadvantage of      216
Bonferroni adjustments, error rates and      533—535
Bonferroni adjustments, F value and      318 344
Bonferroni adjustments, in profile analysis      229
Bonferroni adjustments, in regression analysis      83
Bonferroni adjustments, inequality for      238—239
Bonferroni adjustments, multiple comparisons and      217
Bonferroni adjustments, of critical values      13—14 21 24 45 54 86 213 215—218 481
Bonferroni, C.E.      13 54 187 213
Bonnett, D.G.      6
Bose, R.C.      221
Bower, G.      4 78
Box problem      373—374
Box test      187 190 282

Box, G.E.P.      187 281—282 374
Bradu, D.      244—245
Braver, S.L.      5
Brett, J.M.      124 136
Brien, A.J.      192
Brown, R.      55 467
Browne, M.W.      278
Byrne, B.M.      479—480
C.o.c      See Contrasts contrast
Calculators      66 92 156—101 137 181 212
Calculators, error in      97
Calculus      22 29 32 54 57 63 70
Calculus, matrices and      502—503
Calculus, optimization with      63
CANCORR program      301—304 305
Canned programs      51—52 72 96 159 301—307 487.
Canonical analysis (Canona)      16t 35—38 50 55 56 268—317. Canonical
Canonical analysis (Canona), and other techniques      277—278
Canonical analysis (Canona), as mutual regression      270—271 277 556
Canonical analysis (Canona), attempted via SEM      470—471
Canonical analysis (Canona), CANCORR program      301—304
Canonical analysis (Canona), canned programs      301—307
Canonical analysis (Canona), Canonical cautionary      290—293 414
Canonical analysis (Canona), component analysis      285
Canonical analysis (Canona), demonstration problems      307—317
Canonical analysis (Canona), examples of      274—277 282—284 290—293 301—304
Canonical analysis (Canona), formulae for      268—274
Canonical analysis (Canona), generalization of      279 280—290
Canonical analysis (Canona), heuristic justification of      270—271
Canonical analysis (Canona), likelihood-ratio test and      278 279—280
Canonical analysis (Canona), Manova and      269 277 279 459 557—559
Canonical analysis (Canona), missing significance tests in      295—297 470—471
Canonical analysis (Canona), multiple regression and      277 290 292 295—297
Canonical analysis (Canona), optimization procedure      56 269 298
Canonical analysis (Canona), repeated-battery      284—288
Canonical analysis (Canona), significance tests for      269 270—280 314 317 455
Canonical analysis (Canona), via matrix-manipulation programs      297—301
Canonical analysis (Canona), vs. Multivariate multiple regresion      290
Canonical correlation (canonical R, )      35—38 55 56 268—317
Canonical correlation (canonical R, ), coefficient of      35—38 55 56 271 279
Canonical correlation (canonical R, ), squared      56 269 272 295 298 299 302 310
Canonical variates      37 50 55 56 554—555
Canonical variates, coefficients      268 296
Canonical variates, defined      268—269 272—273
Canonical variates, interpretation of      269 274—277 289—290
Canonical variates, rotation of      288—289
Canonical variates, simplified      269 276 289—290
Canonical variates, testing      235 269—270
Canonical variates, transformations of      289
Carabajal, J.      23
Carets, in notation      322
Carlson, J.E.      115
Carroll, J.B.      362
Carroll, J.D.      280
Cartwright, B.      115
Cathode ray tube (CRT)      87
Cattell, R.B.      408
Cattin, P.      75
Causation, direction of      123
Causation, types of      125 135 136
Ceiling effects      446
Central limit theorem, generalization of      452
Centrality, of traits      68
Centroid analysis      44 406 409
Centroid, as vector of means      184
Chakravarti      234
Chance, capitalization on      75 85 126 146 218
Change score approach to repeated-measures design      39
Characteristic equation      322—323 506
Characteristic root      See Eigenvalues
Characteristic vector      See Eigenvectors
Cheating, attitudes toward      253—255
Cheating, questionnaire on      344t 276—277 367t 369t
Chi-square ( $\chi^2$ ) distribution      76 352 517
Chi-square ( $\chi^2$ ) distribution, and      184
Chi-square ( $\chi^2$ ) distribution, additive components      235
Chi-square ( $\chi^2$ ) distribution, Bonferroni-adjusted      469—474
Chi-square ( $\chi^2$ ) distribution, degrees of freedom      186 187 190
Chi-square ( $\chi^2$ ) distribution, F test substituted for      278
Chi-square ( $\chi^2$ ) distribution, partitioned-U      234—237
Chi-square ( $\chi^2$ ) distribution, Wishart distribution as generalization of      76
Chi-square tests, in known-covariance-matrix case      187
Chi-square tests, h.o.t.d.v.      190
Chi-square tests, homogeneity of covariance matrices      185—187 232 237
Chi-square tests, hypothesis of no non-zero correlations      106
Chi-square tests, Mahalonobis       184
Chi-square tests, of canonical correlations      279—284
Chi-square tests, principal components      353—355 385 392
Chi-square tests, Wilks's lambda and partitions thereof      234—237
Chicano — Anglo differences      23—24 33—34
Chicken game      282—283 283t
Children, testing of      86
Choleski decomposition      See Triangular decomposition
Choosing and interpreting weights for linear combinations      45—51 247 269 276 289—290
Choosing and interpreting weights for linear combinations, average of subset of the measures      45—47
Choosing and interpreting weights for linear combinations, contrast among the measures      47—51
Choosing and interpreting weights for linear combinations, profiles      47
Choosing and interpreting weights for linear combinations, readily interpretable combinations      45—51 247 289—290
Choosing and interpreting weights for linear combinations, sources of ideas for contrasts to be tested      49
Choosing and interpreting weights for linear combinations, subset (kl, k2) contrasts      49—50
Choosing and interpreting weights for linear combinations, translating hypotheses into combining weights      49—51
CI      See Confidence intervals
Cigarettes      274
Class structure, shape of      449
Classification rules, efficiency of      182—184 230—231
Cliff, A.      289
Cliff, N.      452
Cluster analysis      409 480
Coefficient, matrix in PCA and FA      321 329—332 340—341 375 380 423—428 430 431 542
Coefficient, matrix in SEM      477
Coefficient, of multiple correlation      31—32 59
Cofactor method      See Inversion of matrices
Cohen, B.P.      5
Cohen, J.      148
Cohen, P.      148
Coherence, of STPs      234—238
Collins, L.M.      40
Column vectors      488
Combined variables      12 16t 146 222—224 247 251 263 267
Common metric, need for      46—47 67 293—294 449—450
Communality      358 361—363 387 397—406
Communality, approximations to      400—401
Communality, conceptual definition of      396 402 403
Communality, estimating      42 43 398—403
Communality, Heywood cases      402 408 442
Communality, in factor analysis      360—362 397—406
Communality, in rotated component analysis      318
Communality, of variables      43 361—363
Communality, optimal      409
Communality, PCA and      404 416—419 424
Communality, PFA and      404—405 566
Communality, reliabilities and      401 420
Communality, squared multiple correlation and      401—403
Communality, theoretical (minimum-rank) solutions for      398—400
Communality, variance of, in defining simple structure      361
Commutative multiplication      490
Comparisons in       164—165 172—173 179—181 206—208 208t
Comparisons in Anova      213—218
Comparisons in Manova      221—224 222t
Comparisons in MRA      84—86 93—94
Comparisons, counting the number of      217
Complex (imaginary) numbers      400
components      See Principal components
Composite variables      See Combined variables
Compound symmetry      190
Computers, advice on use      98—100
Computers, canned programs      See Canned programs
Computers, enhancement of pictures by      163
Computers, logic and organization of      97—98
Computers, programs for      See Programs computer

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