Statistical principles in experimental design / B.J. Winer, Donald R. Brown, Kenneth M. Michels.
Series McGraw-Hill series in psychologyEditor: New York : McGraw-Hill, c1991Edición: 3rd edDescripción: xiii, 1057 p. : il. ; 25 cmISBN: 0070709823Tema(s): Experimental designOtra clasificación: 62Kxx Recursos en línea: Publisher description | Table of contents1 Introduction to Design [1] 1.1 Introduction [1] 1.2 The Control of Independent, Dependent, and Supplementary Variables [2] 1.3 Experimental Design Basics [6] 1.4 Summary [10] 2 Principles of Estimation and Inference: Means and Variances [12] 2.1 Basic Terminology in Sampling [12] 2.2 Basic Terminology in Statistical Estimation [13] 2.3 Basic Terminology in Testing Statistical Hypotheses [17] 2.4 Variables with Normal Distributions [20] 2.5 Other Distributions—Chi-Square, t, and F [28] 2.6 Inferences Concerning Means [35] 2.7 Inferences Concerning Pairs of Means [51] 3 Design and Analysis of Single-Factor Experiments: Completely Randomized Design [74] 3.1 Introduction [74] 3.2 Definitions and Numerical Example [74] 3.3 Structural Model: Model I (Fixed Constants) [82] 3.4 Methods of Deriving Estimates and Their Expected Values: Model I [89] 3.5 Structural Model—Model II (Variance-Component Model) [92] 3.6 Analysis of Variance Assumptions [100] 3.7 Transformations [110] 3.8 Unequal Sample Sizes [110] 3.9 Power, Treatment Effect Size, and the Determination of Sample Size [120] 3.10 Comparisons Among Treatment Means [140] 3.11 Methods of Error Control for Sets of Multiple Comparisons [153] 3.12 Comparing Comparison Methods [195] 3.13 Treatment Magnitude—Dependent Variable Relationships: Trend Analysis and Strength of Association [198] 3.14 Randomized Complete-Block Designs [210] 3.15 Exercises [216] 4 Single-Factor Experiments Having Repeated Measures on the Same Elements [220] 4.1 Introduction [220] 4.2 Notation and Computational Procedures [222] 4.3 Numerical Example [228] 4.4 Analysis of Variance Assumptions for Repeated Measures Designs [239] 4.5 Statistical Models and the Assumptions [261] 4.6 Measures of Association and Power [274] 4.7 Hotelling’s T2 Multivariate Analysis of Data That Do Not Meet the Circularity Assumption [278] 4.8 Topics Closely Related to Repeated-Measures Anov [281] 4.9 Exercises [282] 5 Design and Analysis of Factorial Experiments: Completely Randomized Designs [284] 5.1 General Purpose [284] 5.2 Terminology and Notation [286] 5.3 Structural Model [291] 5.4 Estimating Elements of the Model [298] 5.5 Principles for Constructing F Ratios [311] 5.6 Higher-Order Factorial Experiments [313] 5.7 Estimation and Tests of Significance for Three-Factor Experiments [323] 5.8 Simple Effects and Their Tests [326] 5.9 Geometric Interpretation of Higher-Order Interactions [333] 5.10 Individual Comparisons [342] 5.11 Partition of Main Effects and Interaction into Trend Components [348] 5.12 The Case n =1 and a Test for Nonadditivity [351] 5.13 The Choice of a Scale of Measurement and Transformations [354] 5.14 Nested Factors (Hierarchal Designs) [358] 5.15 Split-Plot Designs [365] 5.16 Rules for Deriving the Expected Values of Mean Squares [369] 5.17 Quasi F Ratios [374] 5.18 Preliminary Tests on the Model and Pooling Procedures [377] 5.19 Replicated Experiments [382] 5.20 Unequal Cell Frequencies [385] 5.21 Estimation of the Magnitude of Experimental Effects and Statistical Power [405] 5.22 Exercises [416] 6 Factorial Experiments—Computational Procedures and Numerical Examples [419] 6.1 General Purpose [419] 6.2 p x q Factorial Experiment Having n Observations Per Cell [419] 6.3 p x q Factorial Experiment—Unequal Cell Frequencies [438] 6.4 Effect of Scale Measurement on Interaction [442] 6.5 p x q x r Factorial Experiment Having n Observations Per Cell [445] 6.6 Computational Procedures for Nested Factors [456] 6.7 Factorial Experiment with a Single Control Group [460] 6.8 Test for Nonadditivity [465] 6.9 Computation of Trend Components [470] 6.10 General Computational Formulas for Main Effects and Interactions [476] 6.11 Missing Data [479] 6.12 Special Computational Procedures when all Factors have Two Levels [481] 6.13 Unequal Cell Frequencies—Least-Squares Solution [486] 6.14 Analysis of Variance in Terms of Polynomial Progression [492] 6.15 Exercises [492] 7 Multifactor Experiments Having Repeated Measures on the Same Elements [497] 7.1 General Purpose [497] 7.2 Two-Factor Experiment with Repeated Measures on One Factor [509] 7.3 Three-Factor Experiment with Repeated Measures (Case I) [531] 7.4 Three-Factor Experiment with Repeated Measures (Case II) [547] 7.5 Other Multifactor Repeated-Measure Plans [557] 7.6 Tests on Trends [562] 7.7 Unequal Group Size [575] 7.8 Measures of Association and Statistical Power [580] 7.9 Exercises [580] 8 Factorial Experiments in which some of the Interactions are Confounded [583] 8.1 General Purpose [583] 8.2 Assigning Treatments to Blocks [586] 8.3 Methods for Obtaining and Confounding Interaction Components [590] 8.4 Simplified Computational Procedures for 2k Factorial Experiments [603] 8.5 Designs for 2k Experiments [607] 8.6 Designs for 3k Experiments [625] 8.7 Mixed Designs [647] 8.8 Fractional Replications [661] 8.9 Exercises [670] 9 Latin Squares and Related Designs [674] 9.1 Definition and Enumeration of Latin Square [674] 9.2 Uses of Latin Squares [679] 9.3 Analysis of Latin-Square Designs—No Repeated Measures [687] 9.4 Analysis of Greco-Latin Squares [699] 9.5 Analysis of Latin Squares—Repeated Measures [702] 9.6 Exercises [735] 10 Analysis of Covariance [739] 10.1 General Purpose [739] 10.2 Single-Factor Experiment [744] 10.3 Multiple Covariates [788] 10.4 Factorial Experiment [800] 10.5 Analysis of Covariance—Repeated Measures [820] 10.6 Exercises [837] A Random Variables [841] A.l Random Variables and Probability Distributions [842] A.2 Normal distribution [850] A.3 Gamma and Chi-Square Distributions [852] A.4 Beta and F Distributions [856] A.5 Student’s t Distribution [863] A.6 Bivariate Normal Distributions [865] A.7 Multivariate Normal Distribution [868] A. 8 Distribution of Quadratic Forms [873] B Vector and Matrix Algebra [876] B.l Vectors and Matrices [876] B.2 Vector and Matrix Equality [881] B.3 Matrix Transposition [881] B.4 Vector and Matrix Addition and Subtraction [882] B.5 Vector and Matrix Multiplication [883] B.6 Matrix Inversion [894] B.7 Linear Transformations and Solving Linear Equations [902] B.8 Basic Statistical Operations [906] C Linear Models: Regression and the Analysis of Variance [911] C.l Linear Relations: Least-Squares Procedures [912] C.2 Hie General Linear Model [941] C.3 The General Linear Model and the Analysis of Variance [954] D Tables [964] E Topics Closely Related to the Analysis of Variance [1011] E.l Use of Analysis of Variance to Estimate [1011] E.2 Analysis of Variance for Ranked Data [1024] E.3 Dichotomous Data [1027] E.4 Kruskal-Wallis H Test [1028] E.5 Contingency Table with Repeated Measures [1030] E.6 Comparing Treatment Effects with a Control [1034] E.7 General Partition of Degrees of Freedom in a Contingency Table [1036] References [1041] Index [1048]
| Item type | Home library | Call number | Materials specified | Status | Date due | Barcode | Course reserves |
|---|---|---|---|---|---|---|---|
Libros
|
Instituto de Matemática, CONICET-UNS | 62 W7675-3 (Browse shelf) | Available | A-7403 |
Incluye referencias bibliográficas (p. 1041-1047) e índices.
1 Introduction to Design [1] --
1.1 Introduction [1] --
1.2 The Control of Independent, Dependent, and Supplementary Variables [2] --
1.3 Experimental Design Basics [6] --
1.4 Summary [10] --
2 Principles of Estimation and Inference: --
Means and Variances [12] --
2.1 Basic Terminology in Sampling [12] --
2.2 Basic Terminology in Statistical Estimation [13] --
2.3 Basic Terminology in Testing Statistical Hypotheses [17] --
2.4 Variables with Normal Distributions [20] --
2.5 Other Distributions—Chi-Square, t, and F [28] --
2.6 Inferences Concerning Means [35] --
2.7 Inferences Concerning Pairs of Means [51] --
3 Design and Analysis of Single-Factor Experiments: --
Completely Randomized Design [74] --
3.1 Introduction [74] --
3.2 Definitions and Numerical Example [74] --
3.3 Structural Model: Model I (Fixed Constants) [82] --
3.4 Methods of Deriving Estimates and Their Expected Values: Model I [89] --
3.5 Structural Model—Model II (Variance-Component Model) [92] --
3.6 Analysis of Variance Assumptions [100] --
3.7 Transformations [110] --
3.8 Unequal Sample Sizes [110] --
3.9 Power, Treatment Effect Size, and the Determination of Sample Size [120] --
3.10 Comparisons Among Treatment Means [140] --
3.11 Methods of Error Control for Sets of Multiple Comparisons [153] --
3.12 Comparing Comparison Methods [195] --
3.13 Treatment Magnitude—Dependent Variable Relationships: Trend Analysis and Strength of Association [198] --
3.14 Randomized Complete-Block Designs [210] --
3.15 Exercises [216] --
4 Single-Factor Experiments Having Repeated Measures on the Same Elements [220] --
4.1 Introduction [220] --
4.2 Notation and Computational Procedures [222] --
4.3 Numerical Example [228] --
4.4 Analysis of Variance Assumptions for Repeated Measures Designs [239] --
4.5 Statistical Models and the Assumptions [261] --
4.6 Measures of Association and Power [274] --
4.7 Hotelling’s T2 Multivariate Analysis of Data That Do Not Meet the Circularity Assumption [278] --
4.8 Topics Closely Related to Repeated-Measures Anov [281] --
4.9 Exercises [282] --
5 Design and Analysis of Factorial Experiments: Completely Randomized Designs [284] --
5.1 General Purpose [284] --
5.2 Terminology and Notation [286] --
5.3 Structural Model [291] --
5.4 Estimating Elements of the Model [298] --
5.5 Principles for Constructing F Ratios [311] --
5.6 Higher-Order Factorial Experiments [313] --
5.7 Estimation and Tests of Significance for Three-Factor Experiments [323] --
5.8 Simple Effects and Their Tests [326] --
5.9 Geometric Interpretation of Higher-Order Interactions [333] --
5.10 Individual Comparisons [342] --
5.11 Partition of Main Effects and Interaction into Trend Components [348] --
5.12 The Case n =1 and a Test for Nonadditivity [351] --
5.13 The Choice of a Scale of Measurement and Transformations [354] --
5.14 Nested Factors (Hierarchal Designs) [358] --
5.15 Split-Plot Designs [365] --
5.16 Rules for Deriving the Expected Values of Mean Squares [369] --
5.17 Quasi F Ratios [374] --
5.18 Preliminary Tests on the Model and Pooling Procedures [377] --
5.19 Replicated Experiments [382] --
5.20 Unequal Cell Frequencies [385] --
5.21 Estimation of the Magnitude of Experimental Effects and Statistical Power [405] --
5.22 Exercises [416] --
6 Factorial Experiments—Computational Procedures and Numerical Examples [419] --
6.1 General Purpose [419] --
6.2 p x q Factorial Experiment Having n Observations Per Cell [419] --
6.3 p x q Factorial Experiment—Unequal Cell Frequencies [438] --
6.4 Effect of Scale Measurement on Interaction [442] --
6.5 p x q x r Factorial Experiment Having n Observations Per Cell [445] --
6.6 Computational Procedures for Nested Factors [456] --
6.7 Factorial Experiment with a Single Control Group [460] --
6.8 Test for Nonadditivity [465] --
6.9 Computation of Trend Components [470] --
6.10 General Computational Formulas for Main Effects and Interactions [476] --
6.11 Missing Data [479] --
6.12 Special Computational Procedures when all Factors have Two Levels [481] --
6.13 Unequal Cell Frequencies—Least-Squares Solution [486] --
6.14 Analysis of Variance in Terms of Polynomial Progression [492] --
6.15 Exercises [492] --
7 Multifactor Experiments Having Repeated Measures on the Same Elements [497] --
7.1 General Purpose [497] --
7.2 Two-Factor Experiment with Repeated Measures on One Factor [509] --
7.3 Three-Factor Experiment with Repeated Measures (Case I) [531] --
7.4 Three-Factor Experiment with Repeated Measures (Case II) [547] --
7.5 Other Multifactor Repeated-Measure Plans [557] --
7.6 Tests on Trends [562] --
7.7 Unequal Group Size [575] --
7.8 Measures of Association and Statistical Power [580] --
7.9 Exercises [580] --
8 Factorial Experiments in which some of the Interactions are Confounded [583] --
8.1 General Purpose [583] --
8.2 Assigning Treatments to Blocks [586] --
8.3 Methods for Obtaining and Confounding Interaction Components [590] --
8.4 Simplified Computational Procedures for 2k Factorial Experiments [603] --
8.5 Designs for 2k Experiments [607] --
8.6 Designs for 3k Experiments [625] --
8.7 Mixed Designs [647] --
8.8 Fractional Replications [661] --
8.9 Exercises [670] --
9 Latin Squares and Related Designs [674] --
9.1 Definition and Enumeration of Latin Square [674] --
9.2 Uses of Latin Squares [679] --
9.3 Analysis of Latin-Square Designs—No Repeated Measures [687] --
9.4 Analysis of Greco-Latin Squares [699] --
9.5 Analysis of Latin Squares—Repeated Measures [702] --
9.6 Exercises [735] --
10 Analysis of Covariance [739] --
10.1 General Purpose [739] --
10.2 Single-Factor Experiment [744] --
10.3 Multiple Covariates [788] --
10.4 Factorial Experiment [800] --
10.5 Analysis of Covariance—Repeated Measures [820] --
10.6 Exercises [837] --
A Random Variables [841] --
A.l Random Variables and Probability Distributions [842] --
A.2 Normal distribution [850] --
A.3 Gamma and Chi-Square Distributions [852] --
A.4 Beta and F Distributions [856] --
A.5 Student’s t Distribution [863] --
A.6 Bivariate Normal Distributions [865] --
A.7 Multivariate Normal Distribution [868] --
A. 8 Distribution of Quadratic Forms [873] --
B Vector and Matrix Algebra [876] --
B.l Vectors and Matrices [876] --
B.2 Vector and Matrix Equality [881] --
B.3 Matrix Transposition [881] --
B.4 Vector and Matrix Addition and Subtraction [882] --
B.5 Vector and Matrix Multiplication [883] --
B.6 Matrix Inversion [894] --
B.7 Linear Transformations and Solving Linear Equations [902] --
B.8 Basic Statistical Operations [906] --
C Linear Models: Regression and the Analysis of Variance [911] --
C.l Linear Relations: Least-Squares Procedures [912] --
C.2 Hie General Linear Model [941] --
C.3 The General Linear Model and the Analysis of Variance [954] --
D Tables [964] --
E Topics Closely Related to the Analysis of Variance [1011] --
E.l Use of Analysis of Variance to Estimate [1011] --
E.2 Analysis of Variance for Ranked Data [1024] --
E.3 Dichotomous Data [1027] --
E.4 Kruskal-Wallis H Test [1028] --
E.5 Contingency Table with Repeated Measures [1030] --
E.6 Comparing Treatment Effects with a Control [1034] --
E.7 General Partition of Degrees of Freedom in a Contingency Table [1036] --
References [1041] --
Index [1048] --
MR, REVIEW #
Click on an image to view it in the image viewer
There are no comments on this title.