Design and Analysis of Experiments, Volume 1 Introduction to Experimental Design

by Hinkelmann, Klaus; Kempthorne, Oscar

• ISBN13: 9780471727569
• ISBN10: 0471727563
• Edition: 2nd
• Format: Hardcover
• Copyright: 2007-12-17
• Publisher: Wiley-Interscience

Summary

This volume provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments, while also detailing the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions.

Author Biography

Klaus Hinkelmann, PhD, is Emeritus Professor of Statistics in the Department of Statistics at Virginia Polytechnic Institute and State University. A Fellow of the American Statistical Association and the American Association for the Advancement of Science, Dr. Hinkelmann has published extensively in the areas of design of experiments, statistical methods, and biometry.

The late Oscar Kempthorne, ScD, was Emeritus Professor of Statistics and Emeritus Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He was the recipient of many honors within the statistics profession.

Table of Contents

The Processes of Science

Introduction

Development of Theory

The Nature and Role of Theory in Science

Varieties of Theory

The Problem of General Science

Causality

The Upshot

What Is An Experiment?

Statistical Inference

Principles of Experimental Design

Confirmatory and Exploratory Experiments

Steps of Designed Investigations

The Linear Model

Illustrating Individual Steps: Study 1

Three Principles of Experimental Design

The Statistical Triangle and Study 2

Planning the Experiment

Cooperation between Scientist and Statistician

General Principle of Inference

Other Considerations for Experimental Designs

Survey of Designs and Analyses

Introduction

Error-Control Designs

Treatment Designs

Combining Ideas

Sampling Designs

Analysis and Statistical Software

Summary

Linear Model Theory

Introduction

Representation of Linear Models

Functional and Classificatory Linear Models

The Fitting Of Y .= X_

The Moore-Penrose Generalized Inverse

The Conditioned Linear Model

The Two-Part Linear Model

A Special Case of a Partitioned Model

Three-Part Models

The Two-Way Classification Without Interaction

The K-Part Linear Model

Balanced Classificatory Structures

Unbalanced Data Structures

Analysis of Covariance Model

From Data Analysis to Statistical Inference

The Simple Normal Stochastic Linear Model

Distribution Theory with GMNLM

Mixed Models

Randomization

Introduction

The Tea Tasting Lady

A Triangular Experiment

The Simple Arithmetical Experiment

Randomization Ideas for Intervention Experiments

The General Idea of the Experiment Randomization Test

Introduction to Subsequent

The Completely Randomized Design

Introduction and Definition

The Randomization Process

The Derived Linear Model

Analysis Of Variance

Statistical Tests

Approximating the Randomization Test

CRD with Unequal Numbers of Replications

Number of Replications

Subsampling In A CRD

Transformations

Examples Using SASR

Comparisons of Treatments

Introduction

Comparisons for Qualitative Treatments

Orthogonality and Orthogonal Comparisons

Comparisons for Quantitative Treatments

Multiple Comparison Procedures

Grouping Treatments

Examples Using SAS

Use of Supplementary Information

Introduction

Motivation of the Procedure

Analysis of Covariance Procedure

Treatment Comparisons

Violation of Assumptions

Analysis of Covariance with Subsampling

The Case of Several Covariates

Examples Using SAS R

Randomized Block Designs

Introduction

Randomized Complete Block Design

Relative Efficiency of the RCBD

Analysis of Covariance

Missing Observations

Nonadditivity in the RCBD

The Generalized Randomized Block Design

Incomplete Block Designs

Systematic Block Designs

Examples Using SASR

Latin Square Type Designs

Introduction and Motivation

Latin Square Design

Replicated Latin Squares

Latin Rectangles

Incomplete Latin Squares

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