Analysis of Quantal Response Data


Book Description

This book takes the standard methods as the starting point, and then describes a wide range of relatively new approaches and procedures designed to deal with more complicated data and experiments - including much recent research in the area. Throughout mention is given to the computing requirements - facilities available in large computing packages like BMDP, SAS and SPSS are also described.




Statistical Analysis of Ecotoxicity Studies


Book Description

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.







The Analysis of Frequency Data


Book Description

Basic properties of log-linear models; Maximum-likelihood estimation; Numerical evaluation of maximum-likelihood estimates; Asymptotic properties; Complete factorial tables; Social-mobility tables; Incomplete contingency tables; Quantal response models; Some extensions.




Model-robust Quantal Regression


Book Description




POLO


Book Description

Describes the computer program POLO from experimental design, through data input, to program output.




The Use of Non-Linear Regression Methods for Analysing Sensitivity and Quantal Response Data


Book Description

A great many special methods for the statistical analysis of sensitivity or quantal response data have been developed during the past century. This paper demonstrates that many of these techniques can be considered in the light of non-linear regression methods which have been made more tolerable in recent years with the prevalence of high-speed computers.




Quantal Response Analysis in the Absence of a Zone of Mixed Results Using Data Augmentation


Book Description

Quantal response analysis is used to estimate the probability of a dichotomous response, e.g., complete penetration, as a function of a stimulus variable. Using maximum likelihood and the DiDonato-Janagin algorithm, estimates of the normal distribution parameters that underlie threshold stimulus levels are obtainable if a zone of mixed results is observed in the test data and if the average success-producing stimulus exceeds the average failure-producing stimulus. In the absence of a zone of mixed results, a method is proposed that utilizes data augmentation to estimate some parameter of interest, e.g., the probability of success at a specific stimulus level. This method generates artificial copies of the original data set of stimuli and responses and then adds a random noise component to each of the stimuli.