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Book Categories |
| Ch. 1 | Introduction | 1 | |||||||||
| Ch. 2 | Quantal Response Bioassays | 9 | |||||||||
| I | Types of Quantal Response Bioassays | 10 | |||||||||
| II | Experimental Design | 11 | |||||||||
| A | Randomization of Test Subjects | 11 | |||||||||
| B | Controls | 12 | |||||||||
| C | Replication | 12 | |||||||||
| D | Order of Treatments within a Replication | 14 | |||||||||
| References | 15 | ||||||||||
| Ch. 3 | Binary Response with One Explanatory Variable | 17 | |||||||||
| I | Terminology and General Statistical Model | 17 | |||||||||
| II | Data Analyses | 20 | |||||||||
| A | Probit or Logit Analysis | 20 | |||||||||
| 1 | Computer Programs | 22 | |||||||||
| 2 | Sample Computer Output | 23 | |||||||||
| 3 | Interpreting Results of Hypotheses Tests | 31 | |||||||||
| References | 33 | ||||||||||
| Ch. 4 | Binary Response: Design, Fit, and Other Problems | 35 | |||||||||
| I | Experimental Design | 35 | |||||||||
| A | Dose Selection and Sample Size | 35 | |||||||||
| B | Number of Doses | 39 | |||||||||
| II | Goodness-of-Fit | 40 | |||||||||
| III | Lethal Dose Ratios | 42 | |||||||||
| IV | Separation of Probit or Logit Lines into Groups with Equal Response | 45 | |||||||||
| V | Comparison of Lethal Doses | 46 | |||||||||
| VI | Risk of Erroneous Conclusions | 46 | |||||||||
| VII | Alternatives to Probit or Logit Analysis | 47 | |||||||||
| VIII | Conclusions | 47 | |||||||||
| References | 48 | ||||||||||
| Ch. 5 | Binary Response with Multiple Explanatory Variables | 51 | |||||||||
| I | Early Examples and Inefficient Alternatives | 51 | |||||||||
| II | General Statistical Model | 52 | |||||||||
| III | Types of Variables in Multiple Regression Models | 52 | |||||||||
| IV | Computer Programs | 53 | |||||||||
| V | Multiple Probit Analysis: Example from POLO2 | 53 | |||||||||
| A | Statistical Model | 54 | |||||||||
| B | Hypotheses Test | 55 | |||||||||
| VI | Multiple Logit Analysis: Sample of Analysis with GLIM | 60 | |||||||||
| A | Statistical Model | 60 | |||||||||
| B | Hypotheses Tests | 61 | |||||||||
| C | Search for the "Best" Fitting Dose-Mortality Model | 61 | |||||||||
| D | Example: Acephate | 61 | |||||||||
| 1 | Significance of Average Body Weight | 61 | |||||||||
| 2 | Parallelism of the Logit Lines | 63 | |||||||||
| 3 | Best Fitting Logit Line | 63 | |||||||||
| VII | Conclusions | 64 | |||||||||
| References | 64 | ||||||||||
| Ch. 6 | Multiple Explanatory Variables: Body Weight | 67 | |||||||||
| I | Effects of Erroneous Assumptions about Body Weight | 68 | |||||||||
| II | Testing the Hypothesis of Proportional Response | 69 | |||||||||
| III | When Body Weight is a Significant Independent Variable | 70 | |||||||||
| IV | Standardized Bioassay Techniques Involving Weight | 72 | |||||||||
| V | Conclusions | 76 | |||||||||
| References | 77 | ||||||||||
| Ch. 7 | Polytomous (Multinomial) Quantal Response | 79 | |||||||||
| I | Conditional Binomial Model | 80 | |||||||||
| A | Statistical Model | 80 | |||||||||
| B | Estimation of Parameters | 81 | |||||||||
| C | Estimation of Response Probabilities | 81 | |||||||||
| D | Example | 82 | |||||||||
| II | Multinomial Logit Model: MLPACK | 86 | |||||||||
| III | Conclusions | 87 | |||||||||
| References | 88 | ||||||||||
| Ch. 8 | Mixtures | 89 | |||||||||
| I | Independent, Uncorrelated Joint Action of Pesticide Mixtures | 89 | |||||||||
| A | Statistical Model | 90 | |||||||||
| B | Test of Hypothesis of Independent Joint Action | 90 | |||||||||
| C | Mix | 91 | |||||||||
| 1 | Data Input File | 91 | |||||||||
| 2 | Program Output | 93 | |||||||||
| II | Similar (Additive) Joint Action | 94 | |||||||||
| III | Other Theoretical Hypotheses of Joint Action of Pesticides | 94 | |||||||||
| IV | Synergists | 95 | |||||||||
| V | Conclusions | 96 | |||||||||
| References | 96 | ||||||||||
| Ch. 9 | Time as a Variable | 99 | |||||||||
| I | Sampling Designs | 99 | |||||||||
| A | Alternatives | 99 | |||||||||
| B | General Statistical Models | 100 | |||||||||
| II | Analysis of Independent Time-Mortality Data | 100 | |||||||||
| A | Experimental Design | 100 | |||||||||
| B | Limitations and Constraints | 101 | |||||||||
| III | Analysis of Serial Time-Mortality Data | 102 | |||||||||
| A | Experimental Design | 102 | |||||||||
| B | Statistical Methods | 103 | |||||||||
| C | Estimation | 104 | |||||||||
| 1 | Estimation of Response Probabilities | 104 | |||||||||
| 2 | Estimation of Lethal Doses over Time | 104 | |||||||||
| 3 | Example | 105 | |||||||||
| IV | Conclusions | 110 | |||||||||
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Add Pesticide Bioassays with Arthropods, Bioassays with Arthropods, Second Edition explains the statistical bases and analyses for each kind of quantal response bioassay. The new edition of this seminal resource adds chapters on quarantine statistics, host plants, and veterinary pesticides. It i, Pesticide Bioassays with Arthropods to the inventory that you are selling on WonderClubX
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Add Pesticide Bioassays with Arthropods, Bioassays with Arthropods, Second Edition explains the statistical bases and analyses for each kind of quantal response bioassay. The new edition of this seminal resource adds chapters on quarantine statistics, host plants, and veterinary pesticides. It i, Pesticide Bioassays with Arthropods to your collection on WonderClub |