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Myers J.L., Well A.D. — Research design and statistical analysis
Myers J.L., Well A.D. — Research design and statistical analysis



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Íàçâàíèå: Research design and statistical analysis

Àâòîðû: Myers J.L., Well A.D.

Àííîòàöèÿ:

Adopting an intuitive, informal style, this text emphasizes the statistical concepts and assumptions needed to describe and make inferences about real data. The volume's 21 chapters address topics including univariate distributions; the chi-square and F distributions; contrasts among means; trend analysis; repeated- measures designs; hierarchical designs; Latin squares and related designs; correlation and bivariate regression; and multiple regression. Includes major content and organizational revisions from the previous edition. Suitable for graduate and advanced undergraduate students learning about data analysis, as well as for researchers.


ßçûê: en

Ðóáðèêà: Ìàòåìàòèêà/Âåðîÿòíîñòü/Ñòàòèñòèêà è ïðèëîæåíèÿ/

Ñòàòóñ ïðåäìåòíîãî óêàçàòåëÿ: Ãîòîâ óêàçàòåëü ñ íîìåðàìè ñòðàíèö

ed2k: ed2k stats

Èçäàíèå: second edition

Ãîä èçäàíèÿ: 2003

Êîëè÷åñòâî ñòðàíèö: 760

Äîáàâëåíà â êàòàëîã: 05.06.2005

Îïåðàöèè: Ïîëîæèòü íà ïîëêó | Ñêîïèðîâàòü ññûëêó äëÿ ôîðóìà | Ñêîïèðîâàòü ID
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Ïðåäìåòíûé óêàçàòåëü
$SS_{A(adj)}$, $SS_{S/A(adj)}$ and $SS_{total(adj)}$      418—420 see
Achen, C.H.      484—485 729
Additivity      298—299 345—348 see
Adjusted (shrunken) squared multiple correlation coefficient      200—201 577—580
Adjusted total sum of squares      see Analysis of covariance
Ager, J.W.      217 729
Alexander, R.A.      224 548 729 731
Alf, E.F.      587 729
Algina, J.      225 360—361 363 587 729 731 737
Alpha      83—84
Analysis of covariance (Ancova)      6 412—432
Analysis of covariance (ANCOVA) in higher-order designs      431
Analysis of covariance (ANCOVA), $SS_{A(adj)},SS_{S/A(adj)}$, and $SS_{total(adj)}$      418—420
Analysis of covariance (ANCOVA), adjusted means      419 421
Analysis of covariance (ANCOVA), assumptions      422—427
Analysis of covariance (ANCOVA), compared to ANOVA      414—415
Analysis of covariance (ANCOVA), compared with treatment by blocks design      414 428—430
Analysis of covariance (ANCOVA), contrasts in ANCOVA      421—422
Analysis of covariance (ANCOVA), explanation of terms in ANOVA table      420 (table)
Analysis of covariance (ANCOVA), full and restricted models      416—417
Analysis of covariance (ANCOVA), homogeneity of slopes, testing      427—428
Analysis of covariance (ANCOVA), Johnson — Neyman technique      424
Analysis of covariance (ANCOVA), more than one covariate      431—432
Analysis of covariance (ANCOVA), nonequivalent-groups design      425—426
Analysis of covariance (ANCOVA), polynomial analysis of covariance      432
Analysis of covariance (ANCOVA), testing homogeneity of regression slopes      427—428 630—631
Analysis of covariance (ANCOVA), using multiple regression      630—634
Analysis of variance (ANOVA), effect size      see Effect size
Analysis of variance (ANOVA), hierarchical designs      436—453
Analysis of variance (ANOVA), hierarchical designs, calculating sums of squares for nested terms      456
Analysis of variance (ANOVA), hierarchical designs, groups versus individuals      443—445
Analysis of variance (ANOVA), hierarchical designs, groups versus individuals, pseudogroup procedure      444
Analysis of variance (ANOVA), hierarchical designs, groups versus individuals, quasi-F procedure      444—445
Analysis of variance (ANOVA), hierarchical designs, groups-within-treatments design      436—449
Analysis of variance (ANOVA), hierarchical designs, groups-within-treatments design, using a within-groups variable      445—448
Analysis of variance (ANOVA), hierarchical designs, groups-within-treatments design, using repeated measurements      448—449
Analysis of variance (ANOVA), hierarchical designs, items-within-treatments design      436 449—452
Analysis of variance (ANOVA), hierarchical designs, nesting      437
Analysis of variance (ANOVA), hierarchical designs, partitioning the variance and df      437—440
Analysis of variance (ANOVA), hierarchical designs, pooling group and subject variances      441—443
Analysis of variance (ANOVA), hierarchical designs, structural model and expected mean squares      440—442
Analysis of variance (ANOVA), Latin squares and related designs      457—477
Analysis of variance (ANOVA), Latin squares and related designs replicated Latin square design      469—474
Analysis of variance (ANOVA), Latin squares and related designs, digram balanced design      474—476
Analysis of variance (ANOVA), Latin squares and related designs, Greco-Latin square designs      476—477
Analysis of variance (ANOVA), Latin squares and related designs, incorporating several treatment effects into a single square      468—469
Analysis of variance (ANOVA), Latin squares and related designs, missing scores, estimating      465
Analysis of variance (ANOVA), Latin squares and related designs, nonadditivity      465—467
Analysis of variance (ANOVA), Latin squares and related designs, relative efficiency      464—465
Analysis of variance (ANOVA), Latin squares and related designs, selecting a Latin square      459—461
Analysis of variance (ANOVA), Latin squares and related designs, single Latin square      461
Analysis of variance (ANOVA), Latin squares and related designs, standard square      459
Analysis of variance (ANOVA), Latin squares and related designs, structural model      462—463
Analysis of variance (ANOVA), mixed designs      386—408
Analysis of variance (ANOVA), mixed designs, contrasting means      397—401
Analysis of variance (ANOVA), mixed designs, crossed factors      389—390
Analysis of variance (ANOVA), mixed designs, nested factors      389—390
Analysis of variance (ANOVA), mixed designs, one between-subjects and two within-subjects design      406—407
Analysis of variance (ANOVA), mixed designs, partitioning the variance and df      388—390
Analysis of variance (ANOVA), mixed designs, pretest-posttest designs      402—403
Analysis of variance (ANOVA), mixed designs, simple effects      401—402
Analysis of variance (ANOVA), mixed designs, structural model and expected mean squares      390—392
Analysis of variance (ANOVA), mixed designs, two between-subjects and one within-subjects factor      403—406
Analysis of variance (ANOVA), multifactor between-subjects designs      284—336
Analysis of variance (ANOVA), multifactor between-subjects designs, interactions      284 289—291 298-300 325-329
Analysis of variance (ANOVA), multifactor between-subjects designs, main effects      289—293 307 325
Analysis of variance (ANOVA), multifactor between-subjects designs, nonparametric procedures      372—377
Analysis of variance (ANOVA), multifactor between-subjects designs, pooling      332—334
Analysis of variance (ANOVA), multifactor between-subjects designs, simple effects      302—305
Analysis of variance (ANOVA), multifactor between-subjects designs, simple effects and interactions      304—305
Analysis of variance (ANOVA), multifactor between-subjects designs, structural model and expected mean squares      295—296
Analysis of variance (ANOVA), multifactor between-subjects designs, three-factor designs      324—332
Analysis of variance (ANOVA), multifactor between-subjects designs, trend analysis      305—309
Analysis of variance (ANOVA), multifactor between-subjects designs, with unequal cell sizes      319—324 623—629
Analysis of variance (ANOVA), one-factor between-subjects design      191—232
Analysis of variance (ANOVA), one-factor between-subjects design, nonparametric procedures      219—220
Analysis of variance (ANOVA), one-factor between-subjects design, partitioning the variance and df      196—197
Analysis of variance (ANOVA), one-factor between-subjects design, structural model and expected mean squares      201—204
Analysis of variance (ANOVA), one-factor between-subjects design, with unequal group sizes      204
Analysis of variance (ANOVA), power      see Power
Analysis of variance (ANOVA), repeated-measures designs      342—378
Analysis of variance (ANOVA), repeated-measures designs, $S\times A$ design      345
Analysis of variance (ANOVA), repeated-measures designs, additive model      345
Analysis of variance (ANOVA), repeated-measures designs, assumption of sphericity      355—357
Analysis of variance (ANOVA), repeated-measures designs, epsilon-adjusted F test      357—361
Analysis of variance (ANOVA), repeated-measures designs, MANOVA      359—361
Analysis of variance (ANOVA), repeated-measures designs, missing scores, estimating      349—350 465
Analysis of variance (ANOVA), repeated-measures designs, multifactor repeated-measures design      364—370
Analysis of variance (ANOVA), repeated-measures designs, multifactor repeated-measures design, $S\times A\times B$ design, A and B fixed      364—367
Analysis of variance (ANOVA), repeated-measures designs, multifactor repeated-measures design, $S\times A\times B$ design, A fixed and B random      367—370
Analysis of variance (ANOVA), repeated-measures designs, nonadditive model      352—359
Analysis of variance (ANOVA), repeated-measures designs, Tukey's test for nonadditivity      350—352
Analysis of variance (ANOVA), treatment x blocks design      335 412—414
Analysis of variance (ANOVA), treatment x blocks design, blocks, fixed- or random-effects?      724—725
Analysis of variance (ANOVA), treatment x blocks design, compared with Analysis of covariance      428—430
Analysis of variance (ANOVA), trend analysis      see Trend analysis
Anderson, L.R.      217 729
Anscombe's data sets      47 535—536
Anscombe, F.J.      47 351—352 535—536 729
Appelbaum, M.I.      323 626 729 731
Arvey, R.D.      209 736
Assumptions, analysis of covariance      422—427
Assumptions, bivariate normality in inference about correlation      489—490 493—496
Assumptions, consequences of violations      86—89 151—152
Assumptions, homogeneity of variance (homoscedasticity)      158—161
Assumptions, homogeneity of variance (homoscedasticity) for ANOVA      202 220—223
Assumptions, homogeneity of variance (homoscedasticity) for ANOVA, alternative tests when not satisfied      224—226
Assumptions, homogeneity of variance (homoscedasticity) for contrasts      239—241
Assumptions, homogeneity of variance (homoscedasticity) for regression      522 540—541
Assumptions, independence      65 86—88 96—97 123—124
Assumptions, independence in ANOVA      216—217
Assumptions, independence in bivariate regression      541—542
Assumptions, normality      124 178 184—185
Assumptions, normality in ANOVA      217 287—288
Assumptions, regression      522 531—532
Assumptions, sphericity in repeated-measures ANOVA      355—357
Atiqullah, M.      423 729
Autocorrelation plots      217—218
Backward elimination      592 see
Balanda, K.P.      32 729
Bancroft, T.A.      333 442 730 736
bar graphs      25
Bartlett, M.S.      222 729
Barton, C.N.      363 737
Bayes' rule      70 97—99
Belanger, A.      185
Belsley, D.A.      546 585 597 729
Bergman, E.T.      339 739
Bernoulli trials      75
Beta      83—84 568 726
Between-groups mean square      195 198
Between-subjects designs      165 191—192
Bevan, M.F.      217
Binomial distribution      see Distributions
Bishop, Y.M.M.      173 730
Bivariate normal distribution      see Distributions
Bivariate regression      see Regression
Blair, R.C.      86 122 374 730 739
Bless, H.      340 730
Blocking      6 see
BLUE (best linear unbiased estimators)      726
BMI (body mass index)      726
Bohner, G.      340 730
Boik, R.J.      361 730
Bollen, K.A.      593 730
Bonferroni adjustment      245 see
Bonferroni inequality      245
Bootstrapping      494—496
Borden, V.M.      376 737
Bower, G.H.      179 730
Box plots      17—18
Box plots, inner and outer fences      16—17
Box, G.E.P.      357—358 730 735
Bozivich, H.      333 442 473 730 740
Bray, J.H.      370 736
Brodbeck, F.C.      436 730
Brown — Forsythe test      161 185 222—223 723
Brown, M.B.      161 185 222 224 226 257 287 723 730
Bryk, A.S.      551 730
Buchner, A.      149 732
Calibration sample      see Cross-validation
Camp, C.J.      209 736
Capitalization on chance      see Regression
Carlson, J.E.      323 730
Carryover effects      459
Castellan, N.J.      508 510
Centered leverage      585 726 see
Centering      598 see
Central limit theorem      103
Central tendency      11
Chan, Y.      11 739
Chen, Z.      61 75 84 737
Chi-square distribution      see Distributions
Church, J.D.      223 730
Clark, H.H.      370 730
Clark, V.A.      501 732
Clemm, D.S.      250 733
Cleveland, W.      42 730
Clinch, J.J.      221—222 225 730 733
Cochran's Q test      376—377
Cochran, W.G.      222 376 476 531—532 730 740
Coding of categorical variables      615—637 727 see
Coefficient of determination, $r^2$      54—55
Coefficient of multiple determination, $R^2$      200—201 565—580 see
Coefficient of multiple determination, $R^2$, adjusted or shrunken $R^2$      200—201 577—580
Cohen's d, f and $f^2$      see Effect size
Cohen's guidelines for effect size      see Effect size
Cohen, J.      46 121 134—135 146 156—157 201 206 209—210 212 214 317—318 395 491 588 722 726 731
Collinearity      see Multicollinearity Regression
Combination      76 95—96
Combining data across groups      487—488
Comparisons among means      see Contrasts among means
Completely randomized designs      191
Compound symmetry      356—357
Computational formulas      50 197 231—232
Concomitant variable      412
Confidence intervals, relation to hypothesis tests      122—123
Confidence intervals, simultaneous confidence intervals      246
Confidence intervals, using the chi-square distribution to test hypotheses about variance      176—177
Confidence intervals, using the F distribution, for the ratio of two variances      182—184
Confidence intervals, using the F distribution, relation between the confidence interval and hypothesis test      190
Confidence intervals, using the normal distribution for correlations      see Correlation
Confidence intervals, using the normal distribution for the difference between means of correlated samples      117—119
Confidence intervals, using the normal distribution for the difference between means of independent samples      125—126
Confidence intervals, using the normal distribution for the mean of a population distribution      113—114
Confidence intervals, using the normal distribution for the population correlation, $\rho$      492—493 494
Confidence intervals, using the normal distribution for the squared multiple correlation coefficient      585—587
Confidence intervals, using the t distribution for contrasts      162—165
Confidence intervals, using the t distribution for the difference between means of correlated samples      143—145
Confidence intervals, using the t distribution for the difference between means of independent samples      155
Confidence intervals, using the t distribution for the mean of a population distribution      143—145
Confidence intervals, using the t distribution, inference about correlations      see Correlation
Confidence intervals, using the t distribution, inference about regression coefficients      581—582 see
Confounding      4 466
Conover, W.J.      219 372—373 731 735
Contrasts among means      161—165 233—260 297—298 300-303 361—362 397—401 421—422
Contrasts among means in analysis of covariance      421—422
Contrasts among means in repeated-measures designs      161—163 361—362
Contrasts among means, controlling Type 1 error      241—258 261
Contrasts among means, controlling Type 1 error for comparisons of treatment means with a control, Dunnett's test      255—256
Contrasts among means, controlling Type 1 error for tests of all pairwise contrasts, comparing the tests      254—155 261
Contrasts among means, controlling Type 1 error for tests of all pairwise contrasts, Dunnett's T3 test      252 723
Contrasts among means, controlling Type 1 error for tests of all pairwise contrasts, Fisher — Hayter test      252—254
Contrasts among means, controlling Type 1 error for tests of all pairwise contrasts, Fisher's LSD test      252
Contrasts among means, controlling Type 1 error for tests of all pairwise contrasts, Games — Howell test, when variances are unequal      251—252 723
Contrasts among means, controlling Type 1 error for tests of all pairwise contrasts, Tukey — Kramer test when n's are unequal      250—251
Contrasts among means, controlling Type 1 error for tests of all pairwise contrasts, Tukey's HSD test      248—250
Contrasts among means, controlling Type 1 error for tests of families of planned contrasts, Bonferroni, or Dunn — Bonferroni method      244—246
Contrasts among means, controlling Type 1 error for tests of families of planned contrasts, Sidak or Dunn — Sidak method      246
Contrasts among means, controlling Type 1 error for tests of general post hoc contrasts, Scheffe's test      256—257
Contrasts among means, definition      161 234—235
Contrasts among means, error rate per contrast (EC)      242
Contrasts among means, examples of      235
Contrasts among means, family      241
Contrasts among means, familywise error rate (FWE)      234 242
Contrasts among means, independent-groups      163—165 233—260
Contrasts among means, interaction contrasts in multifactonal designs      300—303
Contrasts among means, main effect contrasts in multifactorial designs      297—298
Contrasts among means, mixed-design contrasts      397—401
Contrasts among means, orthogonal contrasts      259—260
Contrasts among means, pairwise comparisons      235
Contrasts among means, planned versus post hoc contrasts      234 243—244
Contrasts among means, simultaneous confidence intervals for      246
Contrasts among means, standardized      162 164
Contrasts among means, sum of squares associated with a contrast      258
Contrasts among means, summary      261 (table)
Contrasts among means, weighting when ns are unequal      237—239
Cook's distance      546—547 585
Cook, A.E.      469 471 473 731
Cook, R.D.      42 547 585 731
Coombs, W.T.      225—226 731
Corbett, A.T.      282
Correction for attenuation of correlation      486
Correlated groups      see also Confidence intervals or Hypothesis tests
Correlated groups or independent groups      165—167
Correlation      44—51 480—512
Correlation, biserial correlation coefficient      505 507
Correlation, Goodman — Kruskal gamma coefficient      505 508—511
Correlation, inference about correlation      489—501
Correlation, inference about correlation, bivariate normality      489—490
Correlation, inference about correlation, bootstrapping      494—496
Correlation, inference about correlation, confidence intervals for $\rho$      492—493 494
Correlation, inference about correlation, Fisher Z transform      492 725—726
Correlation, inference about correlation, inference about correlation matrices      499—501
Correlation, inference about correlation, inference about dependent correlations with MULTICORR      501
Correlation, inference about correlation, inference about independent correlations      497—499
Correlation, inference about correlation, inference about partial and part correlations      503—504
Correlation, inference about correlation, model for inference in correlation      489—491
Correlation, inference about correlation, power      495—496 498 see
Correlation, inference about correlation, testing the hypothesis $H_0$: $\rho=0$      491—493
Correlation, inference about correlation, what if the assumption is violated?      493—496
Correlation, Kendall tau coefficient      505 508—512
Correlation, multiple correlation coefficient      see Regression
Correlation, partial and part (semipartial) correlations      501—504 512
Correlation, Pearson coefficient, r, defined      44—45
Correlation, Pearson coefficient, r, defined, as sample-specific measure      480—485
Correlation, Pearson coefficient, r, defined, combining data across groups      487—488
Correlation, Pearson coefficient, r, defined, constraints in sets of correlations      504
Correlation, Pearson coefficient, r, defined, correction for attenuation      486
Correlation, Pearson coefficient, r, defined, ecological correlations      488—489
Correlation, Pearson coefficient, r, defined, estimate, adjusting for $s_X$      484
Correlation, Pearson coefficient, r, defined, influence plot      48 50
Correlation, Pearson coefficient, r, defined, interpretation of      46—48 481—489
Correlation, Pearson coefficient, r, defined, measurement error and      485—486
Correlation, Pearson coefficient, r, defined, other ways of expressing      48 50
Correlation, Pearson coefficient, r, defined, restriction of range      481—485
Correlation, Pearson coefficient, r, defined, size, and slope and standard error      481—495
Correlation, Pearson coefficient, r, defined, size, and variability in X and Y      481—485
Correlation, phi coefficient      505—507 512
Correlation, point-biserial correlation coefficient      505 512
Correlation, Spearman rho coefficient      48 505 508—509 511—512
Correlation, standard error of estimate in regression      481 see
Correlation, tetrachoric correlation coefficient      505 507 509(table)—511
Correlational study      3
Covariance      50
Covariate      see Analysis of covariance
Cox, G.M.      476 730
Cramer, E.M.      323 626 729 731
Cronbach, L.J.      403 731
Cross comparisons      300—302
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