Components of Variance by Dr Cox
Identifying the sources and measuring the impact of haphazard variations are important in any number of research applications, from clinical trials and genetics to industrial design and psychometric testing. Only in very simple situations can such variations be represented effectively by independent, identically distributed random variables or by random sampling from a hypothetical infinite population. Components of Variance illuminates the complexities of the subject, setting forth its principles with focus on both the development of models for detailed analyses and the statistical techniques themselves. The authors first consider balanced and unbalanced situations, then move to the treatment of non-normal data, beginning with the Poisson and binomial models and followed by extensions to survival data and more general situations. In the final chapter, they discuss ways of extending and assessing various models, including the study of exceedances, the use of nonlinear representations, the study of transformations of the response variable, and the detailed examination of the distributional form of the underlying random variables. Careful signposting and numerous examples from genetic data analysis, clinical trial design, longitudinal data analysis, industrial design, and meta-analysis make this book accessible - and valuable - not only to statisticians but to all applied research scientists who use statistical methods.-
Statistical Inference
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Practical Risk Theory for Actuaries
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Analysis of Survival Data
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Generalized Linear Models with Random Effects
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An Introduction to the Bootstrap
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Queues
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Transformation and Weighting in Regression
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Asymptotic Analysis of Mixed Effects Models
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Statistics for Long-Memory Processes
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Analysis of Infectious Disease Data
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ROC Curves for Continuous Data
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Missing Data in Longitudinal Studies
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Analyzing and Modeling Rank Data
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Stochastic Geometry
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Semimartingales and their Statistical Inference
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Accelerated Life Models
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Statistical Analysis of Spatial and Spatio-Temporal Point Patterns
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Quasi-Least Squares Regression
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Large Covariance and Autocovariance Matrices
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Design and Analysis of Cross-Over Trials
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Analysis of Variance for Functional Data
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Pareto Distributions
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Analysis of Incomplete Multivariate Data
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Simultaneous Inference in Regression
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Gaussian Markov Random Fields
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Sufficient Dimension Reduction
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Markov Models & Optimization
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Multidimensional Scaling
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Biplots
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Analog Est Methods Econometric
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Predictive Inference
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Subjective Probability Models for Lifetimes
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Smoothing Splines
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Bayesian Inference for Partially Identified Models
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Maximum Likelihood Estimation for Sample Surveys
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Mean Field Simulation for Monte Carlo Integration
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Robust Nonparametric Statistical Methods
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Sequential Analysis
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The Statistical Analysis of Multivariate Failure Time Data
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Measuring Statistical Evidence Using Relative Belief
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Sequential Change Detection and Hypothesis Testing
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Statistical Methods for Stochastic Differential Equations
Cox, D.R.; Solomon, P.J.
| SKU | Unavailable |
| ISBN 13 | 9780367395971 |
| ISBN 10 | 0367395975 |
| Title | Components of Variance |
| Author | Dr Cox |
| Series | Chapman And Hall Crc Monographs On Statistics And Applied Probability |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2019-09-05 |
| Number of pages | 184 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |