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E-raamat: Statistical Analysis of Ecotoxicity Studies

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  • Formaat: EPUB+DRM
  • Ilmumisaeg: 05-Jul-2018
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119488811
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Statistical Analysis of Ecotoxicity StudiesSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 05-Jul-2018
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119488811
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A guide to the issues relevant to the design, analysis, and interpretation of toxicity studies that examine chemicals for use in the environment 

Statistical Analysis of Ecotoxicity Studies offers a guide to the design, analysis, and interpretation of a range of experiments that are used to assess the toxicity of chemicals. While the book highlights ecotoxicity studies, the methods presented are applicable to the broad range of toxicity studies. The text contains myriad datasets (from laboratory and field research) that clearly illustrate the book’s topics. The datasets reveal the techniques, pitfalls, and precautions derived from these studies.

The text includes information on recently developed methods for the analysis of severity scores and other ordered responses, as well as extensive power studies of competing tests and computer simulation studies of regression models that offer an understanding of the sensitivity (or lack thereof) of various methods and the quality of parameter estimates from regression models. The authors also discuss the regulatory process indicating how test guidelines are developed and review the statistical methodology in current or pending OECD and USEPA ecotoxicity guidelines. This important guide: 

•    Offers the information needed for the design and analysis to a wide array of ecotoxicity experiments and to the development of international test guidelines used to assess the toxicity of chemicals

•    Contains a thorough examination of the statistical issues that arise in toxicity studies, especially ecotoxicity

•    Includes an introduction to toxicity experiments and statistical analysis basics

•    Includes programs in R and excel

•    Covers the analysis of continuous and Quantal data, analysis of data as well as Regulatory Issues

•    Presents additional topics (Mesocosm and Microplate experiments, mixtures of chemicals, benchmark dose models, and limit tests) as well as software

Written for directors, scientists, regulators, and technicians, Statistical Analysis of Ecotoxicity Studies provides a sound understanding of the technical and practical issues in designing, analyzing, and interpreting toxicity studies to support or challenge chemicals for use in the environment. 

Preface ix
Acknowledgments xi
About the Companion Website xiii
1 An Introduction to Toxicity Experiments
1(18)
1.1 Nature and Purpose of Toxicity Experiments
1(6)
1.2 Regulatory Context for Toxicity Experiments
7(1)
1.3 Experimental Design Basics
8(4)
1.4 Hierarchy of Models for Simple Toxicity Experiments
12(1)
1.5 Biological vs. Statistical Significance
13(2)
1.6 Historical Control Information
15(1)
1.7 Sources of Variation and Uncertainty
15(1)
1.8 Models with More Complex Structure
16(1)
1.9 Multiple Tools to Meet a Variety of Needs or Simple Approaches to Capture Broad Strokes?
16(3)
2 Statistical Analysis Basics
19(28)
2.1 Introduction
19(1)
2.2 NOEC/LOEC
19(5)
2.3 Probability Distributions
24(5)
2.4 Assessing Data for Meeting Model Requirements
29(1)
2.5 Bayesian Methodology
30(1)
2.6 Visual Examination of Data
30(2)
2.7 Regression Models
32(2)
2.8 Biology-Based Models
34(1)
2.9 Discrete Responses
35(2)
2.10 Time-to-Event Data
37(1)
2.11 Experiments with Multiple Controls
38(9)
Exercises
41(6)
3 Analysis of Continuous Data: NOECs
47(42)
3.1 Introduction
47(1)
3.2 Pairwise Tests
47(6)
3.3 Preliminary Assessment of the Data to Select the Proper Method of Analysis
53(9)
3.4 Pairwise Tests When Data do not Meet Normality or Variance Homogeneity Requirements
62(5)
3.5 Trend Tests
67(8)
3.6 Protocol for NOEC Determination of Continuous Response
75(1)
3.7 Inclusion of Random Effects
75(1)
3.8 Alternative Error Structures
76(1)
3.9 Power Analyses of Models
77(12)
Exercises
81(8)
4 Analysis of Continuous Data: Regression
89(34)
4.1 Introduction
89(3)
4.2 Models in Common Use to Describe Ecotoxicity Dose-Response Data
92(3)
4.3 Model Fitting and Estimation of Parameters
95(9)
4.4 Examples
104(8)
4.5 Summary of Model Assessment Tools for Continuous Responses
112(11)
Exercises
114(9)
5 Analysis of Continuous Data with Additional Factors
123(34)
5.1 Introduction
123(1)
5.2 Analysis of Covariance
123(12)
5.3 Experiments with Multiple Factors
135(22)
Exercises
154(3)
6 Analysis of Quantal Data: NOECs
157(24)
6.1 Introduction
157(1)
6.2 Pairwise Tests
157(3)
6.3 Model Assessment for Quantal Data
160(2)
6.4 Pairwise Models that Accommodate Overdispersion
162(3)
6.5 Trend Tests for Quantal Response
165(3)
6.6 Power Comparisons of Tests for Quantal Responses
168(4)
6.7 Zero-Inflated Binomial Responses
172(3)
6.8 Survival- or Age-Adjusted Incidence Rates
175(6)
Exercises
179(2)
7 Analysis of Quantal Data: Regression Models
181(38)
7.1 Introduction
181(1)
7.2 Probit Model
181(7)
7.3 Weibull Model
188(1)
7.4 Logistic Model
188(2)
7.5 Abbott's Formula and Normalization to the Control
190(7)
7.6 Proportions Treated as Continuous Responses
197(1)
7.7 Comparison of Models
198(1)
7.8 Including Time-Varying Responses in Models
199(5)
7.9 Up-and-Down Methods to Estimate LC50
204(2)
7.10 Methods for ECx Estimation When there is Little or no Partial Mortality
206(13)
Exercises
215(4)
8 Analysis of Count Data: NOEC and Regression
219(24)
8.1 Reproduction and Other Nonquantal Count Data
219(1)
8.2 Transformations to Continuous
219(4)
8.3 GLMM and NLME Models
223(5)
8.4 Analysis of Other Types of Count Data
228(15)
Exercises
237(6)
9 Analysis of Ordinal Data
243(16)
9.1 Introduction
243(1)
9.2 Pathology Severity Scores
243(6)
9.3 Developmental Stage
249(10)
Exercises
255(4)
10 Time-to-Event Data
259(16)
10.1 Introduction
259(2)
10.2 Kaplan-Meier Product-Limit Estimator
261(5)
10.3 Cox Regression Proportional Hazards Estimator
266(2)
10.4 Survival Analysis of Grouped Data
268(7)
Exercises
271(4)
11 Regulatory Issues
275(18)
11.1 Introduction
275(1)
11.2 Regulatory Tests
275(1)
11.3 Development of International Standardized Test Guidelines
276(3)
11.4 Strategic Approach to International Chemicals Management (SAICM)
279(1)
11.5 The United Nations Globally Harmonized System of Classification and Labelling of Chemicals (GHS)
279(1)
11.6 Statistical Methods in OECD Ecotoxicity Test Guidelines
279(1)
11.7 Regulatory Testing: Structures and Approaches
279(8)
11.8 Testing Strategies
287(4)
11.9 Nonguideline Studies
291(2)
12 Species Sensitivity Distributions
293(16)
12.1 Introduction
293(1)
12.2 Number, Choice, and Type of Species Endpoints to Include
294(1)
12.3 Choice and Evaluation of Distribution to Fit
294(6)
12.4 Variability and Uncertainty
300(7)
12.5 Incorporating Censored Data in an SSD 302 Exercises
307(2)
13 Studies with Greater Complexity
309(36)
13.1 Introduction
309(1)
13.2 Mesocosm and Mcrocosm Experiments
310(6)
13.3 Microplate Experiments
316(5)
13.4 Errors-in-Variables Regression
321(2)
13.5 Analysis of Mixtures of Chemicals
323(3)
13.6 Benchmark Dose Models
326(1)
13.7 Limit Tests
327(2)
13.8 Minimum Safe Dose and Maximum Unsafe Dose
329(2)
13.9 Toxicokinetics and Toxicodynamics
331(14)
Exercises
343(2)
Appendix 1 Dataset
345(2)
Appendix 2 Mathematical Framework
347(16)
A2.1 Basic Probability Concepts
347(1)
A2.2 Distribution Functions
348(2)
A2.3 Method of Maximum Likelihood
350(2)
A2.4 Bayesian Methodology
352(2)
A2.5 Analysis of Toxicity Experiments
354(4)
A2.6 Newton's Optimization Method
358(1)
A2.7 The Delta Method
359(1)
A2.8 Variance Components
360(3)
Appendix 3 Tables
363(8)
Table A3.1 Studentized Maximum Distribution
364(1)
Table A3.2 Studentized Maximum Modulus Distribution
365(1)
Table A3.3 Linear and Quadratic Contrast Coefficients
366(1)
Table A3.4 Williams' Test ta,k for α = 0.05
367(4)
References 371(14)
Author Index 385(4)
Subject Index 389
JOHN W. GREEN, PHD, PHD is currently a Principal Consultant Biostatistics in DuPont Data Science and Informatics Group. Dr. Green is the lead DuPont statistician developing internal expertise and training in probabilistic risk assessment methods following guidance developed by EUFRAM and has been very active in OECD expert groups developing test guidelines and guidance documents.

TIMOTHY A. SPRINGER, PHD has served as the statistician for Wildlife International, a leading contract ecotoxicology testing laboratory, for over 25 years.

HENRIK HOLBECH, PHD is an Associate Professor in Ecotoxicology at the University of Southern Denmark.
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