Univariate and multivariate general linear models: theory and applications with SAS
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| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
Boca Raton, FL [u.a.]
Chapman & Hall/CRC
2007
|
| Edition: | 2. ed. |
| Series: | Statistics, textbooks and monographs
|
| Subjects: | |
| Online Access: | Table of contents only Publisher description Inhaltsverzeichnis |
| Item Description: | Rev. ed. of: Univariate & multivariate general linear models / Neil H. Timm, Tammy A. Mieczkowski. c1997. Includes bibliographical references (p. 511-535) and indexes |
| Physical Description: | XVII, 549 S. Ill., graph. Darst. 24 cm. + 1 CD-ROM (12 cm) |
| ISBN: | 9781584886341 158488634X |
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MARC
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| 100 | 1 | |a Kim, Kevin |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Univariate and multivariate general linear models |b theory and applications with SAS |c Kevin Kim ; Neil Timm |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a Boca Raton, FL [u.a.] |b Chapman & Hall/CRC |c 2007 | |
| 300 | |a XVII, 549 S. |b Ill., graph. Darst. |c 24 cm. + |e 1 CD-ROM (12 cm) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Statistics, textbooks and monographs | |
| 500 | |a Rev. ed. of: Univariate & multivariate general linear models / Neil H. Timm, Tammy A. Mieczkowski. c1997. | ||
| 500 | |a Includes bibliographical references (p. 511-535) and indexes | ||
| 630 | 0 | 4 | |a SAS (Computer file) |
| 650 | 7 | |a Lineaire modellen |2 gtt | |
| 650 | 7 | |a Multivariate analyse |2 gtt | |
| 650 | 7 | |a SAS (software) |2 gtt | |
| 650 | 7 | |a Univariate methoden |2 gtt | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Linear models (Statistics) |v Textbooks | |
| 650 | 4 | |a Linear models (Statistics) |x Data processing |v Textbooks | |
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Record in the Search Index
| _version_ | 1804136305903271936 |
|---|---|
| adam_text | Contents
List of Tables . xiü
Preface xv
1 Overview of General Linear Model 1
1.1 Introduction .............................. 1
1.2 General Linear Model......................... 1
1.3 Restricted General Linear Model................... 3
1.4 Multivariate Normal Distribution................... 4
1.5 Elementary Properties of Normal Random Variables......... 8
1.6 Hypothesis Testing.......................... 9
1.7 Generating Multivariate Normal Data................ 10
1.8 Assessing Univariate Normality ................... 11
1.8.1 Normally and Nonnormally Distributed Data........ 12
1.8.2 Real Data Example...................... 15
1.9 Assessing Multivariate Normality with Chi-Square Plots...... 15
1.9.1 Multivariate Normal Data .................. 18
1.9.2 Real Data Example...................... 19
1.10 Using SAS INSIGHT......................... 19
1.10.1 Ramus Bone Data ...................... 19
1.10.2 Risk-Taking Behavior Data.................. 21
1.11 Three-Dimensional Plots....................... 23
2 Unrestricted General Linear Models 25
2.1 Introduction.............................. 25
2.2 Linear Models without Restrictions.................. 25
2.3 Hypothesis Testing.......................... 26
. 2.4 Simultaneous Inference........................ 28
2.5 Multiple Linear Regression...................... 30
2.5.1 Classical and Normal Regression Models.......... 31
2.5.2 Random Classical and Jointly Normal Regression Models . 42
vii
yiii_____________________________________________________CONTENTS
2.6 Linear Mixed Models......................... 49
2.7 One-Way Analysis of Variance.................... 53
2.7.1 Unrestricted Full Rank One-Way Design .......... 54
2.7.2 Simultaneous Inference for the One-Way Design...... 56
2.7.3 Multiple Testing....................... 58
2.8 Multiple Linear Regression: Calibration............... 58
2.8.1 Multiple Linear Regression: Prediction........... 68
2.9 Two-Way Nested Designs....................... 70
2.10 Intraclass Covariance Models..................... 72
3 Restricted General Linear Models 77
3.1 Introduction.............................. 77
3.2 Estimation and Hypothesis Testing.................. 77
3.3 Two-Way Factorial Design without Interaction............ 79
3.4 Latin Square Designs......................... 87
3.5 Repeated Measures Designs ..................... 89
3.5.1 Univariate Mixed ANOVA Model, Full Rank Representation
for a Split Plot Design.................... 90
3.5.2 Univariate Mixed Linear Model, Less Than Full Rank Rep-
resentation .......................... 95
3.5.3 Test for Equal Covariance Matrices and for Circularity ... 97
3.6 Analysis of Covariance........................ 100
3.6.1 ANCOVA with One Covariate................ 102
3.6.2 ANCOVA with Two Covariates............... 104
3.6.3 ANCOVA Nested Designs.................. 105
4 Weighted General Linear Models 109
4.1 Introduction.............................. 109
4.2 Estimation and Hypothesis Testing.................. 110
4.3 OLSE versus FGLS.......................... 113
4.4 General Linear Mixed Model Continued............... 114
4.4.1 Example: Repeated Measures Design............ 117
4.4.2 Estimating Degrees of Freedom for F Statistics in GLMMs 118
4.5 Maximum Likelihood Estimation and Fisher s Information Matrix . 119
4.6 WLSE for Data Heteroscedasticity.................. 121
4.7 WLSE for Correlated Errors..................... 124
4.8 FGLS for Categorical Data...................... 127
4.8.1 Overview of the Categorical Data Model .......... 127
4.8.2 Marginal Homogeneity.................... 130
4.8.3 Homogeneity of Proportions................. 132
4.8.4 Independence......................... 138
4.8.5 Univariate Mixed Linear Model, Less Than Full Rank Rep-
resentation.......................... 141
CONTENTS______________________________________________________ix
5 Multivariate General Linear Models 143
5.1 Introduction.............................. 143
5.2 Developing the Model ........................ 143
5.3 Estimation Theory and Hypothesis Testing.............. 145
5.4 Multivariate Regression........................ 152
5.5 Classical and Normal Multivariate Linear Regression Models .... 153
5.6 Jointly Multivariate Normal Regression Model ........... 163
5.7 Multivariate Mixed Models and the Analysis of Repeated Measure-
ments ................................. 171
5.8 Extended Linear Hypotheses..................... 176
5.9 Multivariate Regression: Calibration and Prediction......... 182
5.9.1 Fixed X............................ 182
5.9.2 Random X.......................... 185
5.9.3 Random X, Prediction.................... 186
5.9.4 Overview — Candidate Model................ 186
5.9.5 Prediction and Shrinkage................... 187
5.10 Multivariate Regression: Influential Observations.......... 189
5.10.1 Results and Interpretation .................. 191
5.11 Nonorthogonal MANOVA Designs.................. 192
5.11.1 Unweighted Analysis..................... 197
5.11.2 Weighted Analysis...................... 198
5.12 MANCOVA Designs......................... 200
5.12.1 Overall Tests......................... 200
5.12.2 Tests of Additional Information............... 203
5.12.3 Results and Interpretation.................. 204
5.13 Stepdown Analysis.......................... 206
5.14 Repeated Measures Analysis..................... 207
5.14.1 Results and Interpretation.................. 209
5.15 Extended Linear Hypotheses..................... 216
5.15.1 Results and Interpretation.................. 219
6 Doubly Multivariate Linear Model 223
6.1 Introduction.............................. 223
6.2 Classical Model Development.................... 223
6.3 Responsewise Model Development.................. 226
6.4 The Multivariate Mixed Model.................... 227
6.5 Double Multivariate and Mixed Models............... 231
7 Restricted MGLM and Growth Curve Model 243
7.1 Introduction.............................. 243
7.2 Restricted Multivariate General Linear Model............ 243
7.3 The GMANOVA Model ....................... 247
7.4 Canonical Form of the GMANOVA Model.............. 254
7.5 Restricted Nonorthogonal Three-Factor Factorial MANOVA .... 259
7.5.1 Results and Interpretation.................. 269
CONTENTS
7.6 Restricted Intraclass Covariance Design............... 269
7.6.1 Results and Interpretation............ 275
7.7 Growth Curve Analysis.................... 279
7.7.1 Results and Interpretation........... 283
7.8 Multiple Response Growth Curves............. 289
7.8.1 Results and Interpretation............... 290
7.9 Single Growth Curve........................ 294
7.9.1 Results and Interpretation............... 294
8 SUR Model and Restricted GMANOVA Model 297
8.1 Introduction.................. 297
8.2 MANOVA-GMANOVA Model ........[[[........ 297
8.3 Tests of Fit.............................. 303
8.4 Sum of Profiles and CGMANOVA Models...... 305
8.5 SUR Model.............................. 307
8.6 Restricted GMANOVA Model.......... ......... 314
8.7 GMANOVA-SUR: One Population ................. 317
8.7.1 Results and Interpretation.............. 317
8.8 GMANOVA-SUR: Several Populations............. . . 319
8.8.1 Results and Interpretation.......... 319
8.9 SUR Model..............................! 319
8.9.1 Results and Interpretation.................. 323
8.10 Two-Period Crossover Design with Changing Covariates...... 328
8.10.1 Results and Interpretation.................. 329
8.11 Repeated Measurements with Changing Covariates......... 334
8.11.1 Results and Interpretation.................. 335
8.12 MANOVA-GMANOVA Model .............. . . . . . 337
8.12.1 Results and Interpretation............. 33g
8.13 CGMANOVA Model.........................! 344
8.13.1 Results and Interpretation................ 347
9 Simultaneous Inference Using Finite Intersection Tests 349
9.1 Introduction...................... 340
9.2 Finite Intersection Tests................ 340
9.3 Finite Intersection Tests of Univariate Means 35O
9.4 Finite Intersection Tests for Linear Models......... 354
9.5 Comparison of Some Tests of Univariate Means with the HT Procedure355
9.5.1 Single-Step Methods........... 355
9.5.2 Stepdown Methods............ 357
9.6 Analysis of Means Analysis ........... ...... 350
9.7 Simultaneous Test Procedures for Mean Vectors 360
9.8 Finite Intersection Test of Mean Vectors..... ....... 362
9.9 Finite Intersection Test of Mean Vectors with Covariates . . . . 366
9.10 Summary................ ..... -,„
9.11 Univariate: One-Way ANOVA.........[ [......... 369
CONTENTS____________________________________________________________xi
9.12 Multivariate: One-Way MANOVA.................. 372
9.13 Multivariate: One-Way MANCOVA................. 379
10 Computing Power for Univariate and Multivariate GLM 381
10.1 Introduction.............................. 381
10.2 Power for Univariate GLMs ..................... 383
10.3 Estimating Power, Sample Size, and Effect Size for the GLM .... 384
10.3.1 Power and Sample Size.................... 384
10.3.2 Effect Size.......................... 385
10.4 Power and Sample Size Based on Interval-Estimation........ 388
10.5 Calculating Power and Sample Size for Some Mixed Models .... 390
10.5.1 Random One-Way ANOVA Design............. 390
10.5.2 Two Factor Mixed Nested ANOVA Design......... 396
10.6 Power for Multivariate GLMs .................... 400
10.7 Power and Effect Size Analysis for Univariate GLMs........ 401
10.7.1 One-Way ANOVA...................... 401
10.7.2 Three-Way ANOVA..................... 403
10.7.3 One-Way ANCOVA Design with Two Covariates...... 405
10.8 Power and Sample Size Based on Interval-Estimation........ 405
10.8.1 One-Way ANOVA...................... 407
10.9 Power Analysis for Multivariate GLMs ............... 409
10.9.1 Two Groups.......................... 409
10.9.2 Repeated Measures Design.................. 409
11 Two-Level Hierarchical Linear Models 413
11.1 Introduction.............................. 413
11.2 Two-Level Hierarchical Linear Models................ 413
11.3 Random Coefficient Model: One Population............. 424
11.4 Random Coefficient Model: Several Populations........... 431
11.5 Mixed Model Repeated Measures .................. 440
11.6 Mixed Model Repeated Measures with Changing Covariates .... 442
11.7 Application: Two-Level Hierarchical Linear Models......... 443
12 Incomplete Repeated Measurement Data 455
12.1 Introduction.............................. 455
12.2 Missing Mechanisms......................... 456
12.3 FGLS Procedure ........................... 457
12.4 ML Procedure............................. 460
12.5 Imputations.............................. 461
12.5.1 EM Algorithm........................ 462
12.5.2 Multiple Imputation ..................... 463
12.6 Repeated Measures Analysis..................... 464
12.7 Repeated Measures with Changing Covariates............ 464
12.8 Random Coefficient Model...................... 467
12.9 Growth Curve Analysis........................ 471
xü______________________________________________________CONTENTS
13 Structural Equation Modeling 479
13.1 Introduction.............................. 479
13.2 Model Notation............................ 481
13.3 Estimation............................... 489
13.4 Model Fit in Practice......................... 494
13.5 Model Modification.......................... 496
13.6 Summary............................... 498
13.7 Path Analysis............................. 499
13.8 Confirmatory Factor Analysis..................... 503
13.9 General SEM............................. 503
References 511
Author Index 537
Subject Index 545
|
| adam_txt |
Contents
List of Tables . xiü
Preface xv
1 Overview of General Linear Model 1
1.1 Introduction . 1
1.2 General Linear Model. 1
1.3 Restricted General Linear Model. 3
1.4 Multivariate Normal Distribution. 4
1.5 Elementary Properties of Normal Random Variables. 8
1.6 Hypothesis Testing. 9
1.7 Generating Multivariate Normal Data. 10
1.8 Assessing Univariate Normality . 11
1.8.1 Normally and Nonnormally Distributed Data. 12
1.8.2 Real Data Example. 15
1.9 Assessing Multivariate Normality with Chi-Square Plots. 15
1.9.1 Multivariate Normal Data . 18
1.9.2 Real Data Example. 19
1.10 Using SAS INSIGHT. 19
1.10.1 Ramus Bone Data . 19
1.10.2 Risk-Taking Behavior Data. 21
1.11 Three-Dimensional Plots. 23
2 Unrestricted General Linear Models 25
2.1 Introduction. 25
2.2 Linear Models without Restrictions. 25
2.3 Hypothesis Testing. 26
. 2.4 Simultaneous Inference. 28
2.5 Multiple Linear Regression. 30
2.5.1 Classical and Normal Regression Models. 31
2.5.2 Random Classical and Jointly Normal Regression Models . 42
vii
yiii_CONTENTS
2.6 Linear Mixed Models. 49
2.7 One-Way Analysis of Variance. 53
2.7.1 Unrestricted Full Rank One-Way Design . 54
2.7.2 Simultaneous Inference for the One-Way Design. 56
2.7.3 Multiple Testing. 58
2.8 Multiple Linear Regression: Calibration. 58
2.8.1 Multiple Linear Regression: Prediction. 68
2.9 Two-Way Nested Designs. 70
2.10 Intraclass Covariance Models. 72
3 Restricted General Linear Models 77
3.1 Introduction. 77
3.2 Estimation and Hypothesis Testing. 77
3.3 Two-Way Factorial Design without Interaction. 79
3.4 Latin Square Designs. 87
3.5 Repeated Measures Designs . 89
3.5.1 Univariate Mixed ANOVA Model, Full Rank Representation
for a Split Plot Design. 90
3.5.2 Univariate Mixed Linear Model, Less Than Full Rank Rep-
resentation . 95
3.5.3 Test for Equal Covariance Matrices and for Circularity . 97
3.6 Analysis of Covariance. 100
3.6.1 ANCOVA with One Covariate. 102
3.6.2 ANCOVA with Two Covariates. 104
3.6.3 ANCOVA Nested Designs. 105
4 Weighted General Linear Models 109
4.1 Introduction. 109
4.2 Estimation and Hypothesis Testing. 110
4.3 OLSE versus FGLS. 113
4.4 General Linear Mixed Model Continued. 114
4.4.1 Example: Repeated Measures Design. 117
4.4.2 Estimating Degrees of Freedom for F Statistics in GLMMs 118
4.5 Maximum Likelihood Estimation and Fisher's Information Matrix . 119
4.6 WLSE for Data Heteroscedasticity. 121
4.7 WLSE for Correlated Errors. 124
4.8 FGLS for Categorical Data. 127
4.8.1 Overview of the Categorical Data Model . 127
4.8.2 Marginal Homogeneity. 130
4.8.3 Homogeneity of Proportions. 132
4.8.4 Independence. 138
4.8.5 Univariate Mixed Linear Model, Less Than Full Rank Rep-
resentation. 141
CONTENTS_ix
5 Multivariate General Linear Models 143
5.1 Introduction. 143
5.2 Developing the Model . 143
5.3 Estimation Theory and Hypothesis Testing. 145
5.4 Multivariate Regression. 152
5.5 Classical and Normal Multivariate Linear Regression Models . 153
5.6 Jointly Multivariate Normal Regression Model . 163
5.7 Multivariate Mixed Models and the Analysis of Repeated Measure-
ments . 171
5.8 Extended Linear Hypotheses. 176
5.9 Multivariate Regression: Calibration and Prediction. 182
5.9.1 Fixed X. 182
5.9.2 Random X. 185
5.9.3 Random X, Prediction. 186
5.9.4 Overview — Candidate Model. 186
5.9.5 Prediction and Shrinkage. 187
5.10 Multivariate Regression: Influential Observations. 189
5.10.1 Results and Interpretation . 191
5.11 Nonorthogonal MANOVA Designs. 192
5.11.1 Unweighted Analysis. 197
5.11.2 Weighted Analysis. 198
5.12 MANCOVA Designs. 200
5.12.1 Overall Tests. 200
5.12.2 Tests of Additional Information. 203
5.12.3 Results and Interpretation. 204
5.13 Stepdown Analysis. 206
5.14 Repeated Measures Analysis. 207
5.14.1 Results and Interpretation. 209
5.15 Extended Linear Hypotheses. 216
5.15.1 Results and Interpretation. 219
6 Doubly Multivariate Linear Model 223
6.1 Introduction. 223
6.2 Classical Model Development. 223
6.3 Responsewise Model Development. 226
6.4 The Multivariate Mixed Model. 227
6.5 Double Multivariate and Mixed Models. 231
7 Restricted MGLM and Growth Curve Model 243
7.1 Introduction. 243
7.2 Restricted Multivariate General Linear Model. 243
7.3 The GMANOVA Model . 247
7.4 Canonical Form of the GMANOVA Model. 254
7.5 Restricted Nonorthogonal Three-Factor Factorial MANOVA . 259
7.5.1 Results and Interpretation. 269
CONTENTS
7.6 Restricted Intraclass Covariance Design. 269
7.6.1 Results and Interpretation. 275
7.7 Growth Curve Analysis. 279
7.7.1 Results and Interpretation. 283
7.8 Multiple Response Growth Curves. 289
7.8.1 Results and Interpretation. 290
7.9 Single Growth Curve. 294
7.9.1 Results and Interpretation. 294
8 SUR Model and Restricted GMANOVA Model 297
8.1 Introduction. 297
8.2 MANOVA-GMANOVA Model .[[[. 297
8.3 Tests of Fit. 303
8.4 Sum of Profiles and CGMANOVA Models. 305
8.5 SUR Model. 307
8.6 Restricted GMANOVA Model. . 314
8.7 GMANOVA-SUR: One Population . 317
8.7.1 Results and Interpretation. 317
8.8 GMANOVA-SUR: Several Populations. . . 319
8.8.1 Results and Interpretation. 319
8.9 SUR Model.! 319
8.9.1 Results and Interpretation. 323
8.10 Two-Period Crossover Design with Changing Covariates. 328
8.10.1 Results and Interpretation. 329
8.11 Repeated Measurements with Changing Covariates. 334
8.11.1 Results and Interpretation. 335
8.12 MANOVA-GMANOVA Model .'.'.'.'.'. 337
8.12.1 Results and Interpretation. 33g
8.13 CGMANOVA Model.! 344
8.13.1 Results and Interpretation. 347
9 Simultaneous Inference Using Finite Intersection Tests 349
9.1 Introduction. 340
9.2 Finite Intersection Tests. 340
9.3 Finite Intersection Tests of Univariate Means 35O
9.4 Finite Intersection Tests for Linear Models. 354
9.5 Comparison of Some Tests of Univariate Means with the HT Procedure355
9.5.1 Single-Step Methods. 355
9.5.2 Stepdown Methods. 357
9.6 Analysis of Means Analysis . . 350
9.7 Simultaneous Test Procedures for Mean Vectors 360
9.8 Finite Intersection Test of Mean Vectors. . 362
9.9 Finite Intersection Test of Mean Vectors with Covariates . . . . 366
9.10 Summary. . -,„
9.11 Univariate: One-Way ANOVA.[ [. 369
CONTENTS_xi
9.12 Multivariate: One-Way MANOVA. 372
9.13 Multivariate: One-Way MANCOVA. 379
10 Computing Power for Univariate and Multivariate GLM 381
10.1 Introduction. 381
10.2 Power for Univariate GLMs . 383
10.3 Estimating Power, Sample Size, and Effect Size for the GLM . 384
10.3.1 Power and Sample Size. 384
10.3.2 Effect Size. 385
10.4 Power and Sample Size Based on Interval-Estimation. 388
10.5 Calculating Power and Sample Size for Some Mixed Models . 390
10.5.1 Random One-Way ANOVA Design. 390
10.5.2 Two Factor Mixed Nested ANOVA Design. 396
10.6 Power for Multivariate GLMs . 400
10.7 Power and Effect Size Analysis for Univariate GLMs. 401
10.7.1 One-Way ANOVA. 401
10.7.2 Three-Way ANOVA. 403
10.7.3 One-Way ANCOVA Design with Two Covariates. 405
10.8 Power and Sample Size Based on Interval-Estimation. 405
10.8.1 One-Way ANOVA. 407
10.9 Power Analysis for Multivariate GLMs . 409
10.9.1 Two Groups. 409
10.9.2 Repeated Measures Design. 409
11 Two-Level Hierarchical Linear Models 413
11.1 Introduction. 413
11.2 Two-Level Hierarchical Linear Models. 413
11.3 Random Coefficient Model: One Population. 424
11.4 Random Coefficient Model: Several Populations. 431
11.5 Mixed Model Repeated Measures . 440
11.6 Mixed Model Repeated Measures with Changing Covariates . 442
11.7 Application: Two-Level Hierarchical Linear Models. 443
12 Incomplete Repeated Measurement Data 455
12.1 Introduction. 455
12.2 Missing Mechanisms. 456
12.3 FGLS Procedure . 457
12.4 ML Procedure. 460
12.5 Imputations. 461
12.5.1 EM Algorithm. 462
12.5.2 Multiple Imputation . 463
12.6 Repeated Measures Analysis. 464
12.7 Repeated Measures with Changing Covariates. 464
12.8 Random Coefficient Model. 467
12.9 Growth Curve Analysis. 471
xü_CONTENTS
13 Structural Equation Modeling 479
13.1 Introduction. 479
13.2 Model Notation. 481
13.3 Estimation. 489
13.4 Model Fit in Practice. 494
13.5 Model Modification. 496
13.6 Summary. 498
13.7 Path Analysis. 499
13.8 Confirmatory Factor Analysis. 503
13.9 General SEM. 503
References 511
Author Index 537
Subject Index 545 |
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| discipline | Informatik Mathematik |
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| edition | 2. ed. |
| format | Book |
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| id | DE-604.BV022291672 |
| illustrated | Illustrated |
| index_date | 2024-07-02T16:51:59Z |
| indexdate | 2024-07-09T20:54:18Z |
| institution | BVB |
| isbn | 9781584886341 158488634X |
| language | English |
| lccn | 2006026561 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015501842 |
| oclc_num | 70921505 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM DE-20 |
| owner_facet | DE-91G DE-BY-TUM DE-20 |
| physical | XVII, 549 S. Ill., graph. Darst. 24 cm. + 1 CD-ROM (12 cm) |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Chapman & Hall/CRC |
| record_format | marc |
| series2 | Statistics, textbooks and monographs |
| spelling | Kim, Kevin Verfasser aut Univariate and multivariate general linear models theory and applications with SAS Kevin Kim ; Neil Timm 2. ed. Boca Raton, FL [u.a.] Chapman & Hall/CRC 2007 XVII, 549 S. Ill., graph. Darst. 24 cm. + 1 CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier Statistics, textbooks and monographs Rev. ed. of: Univariate & multivariate general linear models / Neil H. Timm, Tammy A. Mieczkowski. c1997. Includes bibliographical references (p. 511-535) and indexes SAS (Computer file) Lineaire modellen gtt Multivariate analyse gtt SAS (software) gtt Univariate methoden gtt Datenverarbeitung Linear models (Statistics) Textbooks Linear models (Statistics) Data processing Textbooks Verallgemeinertes lineares Modell (DE-588)4124382-1 gnd rswk-swf SAS Programm (DE-588)4195685-0 gnd rswk-swf Verallgemeinertes lineares Modell (DE-588)4124382-1 s DE-604 SAS Programm (DE-588)4195685-0 s Timm, Neil H. Sonstige (DE-588)124033717 oth http://www.loc.gov/catdir/toc/ecip0619/2006026561.html Table of contents only http://www.loc.gov/catdir/enhancements/fy0668/2006026561-d.html Publisher description HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015501842&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Kim, Kevin Univariate and multivariate general linear models theory and applications with SAS SAS (Computer file) Lineaire modellen gtt Multivariate analyse gtt SAS (software) gtt Univariate methoden gtt Datenverarbeitung Linear models (Statistics) Textbooks Linear models (Statistics) Data processing Textbooks Verallgemeinertes lineares Modell (DE-588)4124382-1 gnd SAS Programm (DE-588)4195685-0 gnd |
| subject_GND | (DE-588)4124382-1 (DE-588)4195685-0 |
| title | Univariate and multivariate general linear models theory and applications with SAS |
| title_auth | Univariate and multivariate general linear models theory and applications with SAS |
| title_exact_search | Univariate and multivariate general linear models theory and applications with SAS |
| title_exact_search_txtP | Univariate and multivariate general linear models theory and applications with SAS |
| title_full | Univariate and multivariate general linear models theory and applications with SAS Kevin Kim ; Neil Timm |
| title_fullStr | Univariate and multivariate general linear models theory and applications with SAS Kevin Kim ; Neil Timm |
| title_full_unstemmed | Univariate and multivariate general linear models theory and applications with SAS Kevin Kim ; Neil Timm |
| title_short | Univariate and multivariate general linear models |
| title_sort | univariate and multivariate general linear models theory and applications with sas |
| title_sub | theory and applications with SAS |
| topic | SAS (Computer file) Lineaire modellen gtt Multivariate analyse gtt SAS (software) gtt Univariate methoden gtt Datenverarbeitung Linear models (Statistics) Textbooks Linear models (Statistics) Data processing Textbooks Verallgemeinertes lineares Modell (DE-588)4124382-1 gnd SAS Programm (DE-588)4195685-0 gnd |
| topic_facet | SAS (Computer file) Lineaire modellen Multivariate analyse SAS (software) Univariate methoden Datenverarbeitung Linear models (Statistics) Textbooks Linear models (Statistics) Data processing Textbooks Verallgemeinertes lineares Modell SAS Programm |
| url | http://www.loc.gov/catdir/toc/ecip0619/2006026561.html http://www.loc.gov/catdir/enhancements/fy0668/2006026561-d.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015501842&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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