Modelling Binary Data Collett Pdf



Author: David Collett

Model for binary data using a small number of hidden. Modelling binary data pdf Model that incorporates hidden binary spin variables, and in principle, it microwave engineering pozar pdf download should be. Modelling binary data Binary Response Data - Logistic Regression Model. Click on the article title to read more. Models for binary and binomial data 45 3.1 Statistical modelling 45 3.2 Linear models 47 3.3 Methods of estimation 50 3.4 Fitting linear models to binomial data 53 3.5 Models for binomial response data 56 3.6 The linear logistic model 58 3.7 Fitting the linear logistic model to binomial data 59 3.8 Goodness of fit of a linear logistic model 65.

Free eBook Modelling Binary Data Second Edition Chapman And Hall Crc Texts In Statistical Science Uploaded By James Patterson, modelling binary data second edition chapman hall crc texts in statistical science 2nd edition by collett david 2002 paperback isbn kostenloser versand fur alle bucher mit versand und verkauf duch. INTRODUCTION: #1 Modelling Binary Data Second Edition Publish By Evan Hunter, Modelling Binary Data Second Edition Chapman Hall Crc modelling binary data second edition chapman hall crc texts in statistical science 2nd edition by collett david 2002 paperback isbn kostenloser versand fur alle bucher mit versand und verkauf duch amazon.

Publisher: CRC Press

ISBN: 1420057383

Category: Mathematics

Page: 408

View: 8056


Since the original publication of the bestselling Modelling Binary Data, a number of important methodological and computational developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to an exact version of logistic regression form valuable additions to the statistician's toolbox, and author Dave Collett has fully updated his popular treatise to incorporate these important advances. Modelling Binary Data, Second Edition now provides an even more comprehensive and practical guide to statistical methods for analyzing binary data. Along with thorough revisions to the original material-now independent of any particular software package- it includes a new chapter introducing mixed models for binary data analysis and another on exact methods for modelling binary data. The author has also added material on modelling ordered categorical data and provides a summary of the leading software packages. All of the data sets used in the book are available for download from the Internet, and the appendices include additional data sets useful as exercises.
Fler böcker inom
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
408
Utgivningsdatum
2002-09-01
Upplaga
2 New edition
Förlag
Chapman & Hall/CRC
Medarbetare
Collett, David / Collett, Collett
Illustratör/Fotograf
index references
Illustrationer
96 Tables, black and white; 54 Illustrations, black and white
Dimensioner
234 x 156 x 21 mm
Vikt
580 g
Antal komponenter
1
Komponenter
Contains 56 Paperback / softbacks
ISBN
9781584883241

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Since the original publication of the bestselling Modelling Binary Data, a number of important methodological and computational developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to an exact version of logistic regression form valuable additions to the statistician's toolbox, and author Dave Collett has fully updated his popular treatise to incorporate these important advances. Modelling Binary Data, Second Edition now provides an even more comprehensive and practical guide to statistical methods for analyzing binary data. Along with thorough revisions to the original material-now independent of any particular software package- it includes a new chapter introducing mixed models for binary data analysis and another on exact methods for modelling binary data. The author has also added material on modelling ordered categorical data and provides a summary of the leading software packages. All of the data sets used in the book are available for download from the Internet, and the appendices include additional data sets useful as exercises.

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De som köpt den här boken har ofta också köpt Modelling Survival Data in Medical Research av David Collett (inbunden).

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Define Binary Data

Kundrecensioner

  • Modelling Survival Data in Medical Research

    Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research. Well known for its nontechnical style, this third edition contains new chapters ...

Praise for the first edition: '...A merit of the book, considerably enhancing its practical value, is the detailed discussion of computational issues and software. ... Overall the book provides an accessible and effective presentation of the topic. I recommend it.' -Journal of Applied Statistics 'In summary, this book draws together material on many practical aspects of the analysis of binary data, which was unavailable before in a single book. Applied statisticians, at any level, will learn something from it.' -The Statistician '...well written, contains good examples, and ideas and concepts are developed and explained logically and clearly...I can strongly recommend this book as a handy reference for applied statisticians and other researchers with a good background in statistical methods... I also appreciated having a book that seems to have very few errors of any kind!' -Biometrics

Modelling Binary Data Collett Pdf Files

INTRODUCTION Some Examples The Scope of this Book Use of Statistical Software STATISTICAL INFERENCE FOR BINARY DATA The Binomial Distribution Inference about the Success Probability Comparison of Two Proportions Comparison of Two or More Proportions MODELS FOR BINARY AND BINOMIAL DATA Statistical Modelling Linear Models Methods of Estimation Fitting Linear Models to Binomial Data Models for Binomial Response Data The Linear Logistic Model Fitting the Linear Logistic Model to Binomial Data Goodness of Fit of a Linear Logistic Model Comparing Linear Logistic Models Linear Trend in Proportions Comparing Stimulus-Response Relationships Non-Convergence and Overfitting Some other Goodness of Fit Statistics Strategy for Model Selection Predicting a Binary Response Probability BIOASSAY AND SOME OTHER APPLICATIONS The Tolerance Distribution Estimating an Effective Dose Relative Potency Natural Response Non-Linear Logistic Regression Models Applications of the Complementary Log-Log Model MODEL CHECKING Definition of Residuals Checking the Form of the Linear Predictor Checking the Adequacy of the Link Function Identification of Outlying Observations Identification of Influential Observations Checking the Assumption of a Binomial Distribution Model Checking for Binary Data Summary and Recommendations OVERDISPERSION Potential Causes of Overdispersion Modelling Variability in Response Probabilities Modelling Correlation Between Binary Responses Modelling Overdispersed Data A Model with a Constant Scale Parameter The Beta-Binomial Model Discussion MODELLING DATA FROM EPIDEMIOLOGICAL STUDIES Basic Designs for Aetiological Studies Measures of Association Between Disease and Exposure Confounding and Interaction The Linear Logistic Model for Data from Cohort Studies Interpreting the Parameters in a Linear Logistic Model The Linear Logistic Model for Data from Case-Control Studies Matched Case-Control Studies MIXED MODELS FOR BINARY DATA Fixed and Random Effects Mixed Models for Binary Data Multilevel Modelling Mixed Models for Longitudinal Data Analysis Mixed Models in Meta-Analysis Modelling Overdispersion Using Mixed Models EXACT METHODS Comparison of Two Proportions Using an Exact Test Exact Logistic Regression for a Single Parameter Exact Hypothesis Tests Exact Confidence Limits for bk Exact Logistic Regression for a Set of Parameters Some Examples Discussion SOME ADDITIONAL TOPICS Ordered Categorical Data Analysis of Proportions and Percentages Analysis of Rates Analysis of Binary Time Series Modelling Errors in the Measurement of Explanatory Variables Multivariate Binary Data Analysis of Binary Data from Cross-Over Trials Experimental Design COMPUTER SOFTWARE FOR MODELLING BINARY DATA Statistical Packages for Modelling Binary Data Interpretation of Computer Output Using Packages to Perform Some Non-Standard Analyses Appendix A: Values of logit(p) and probit(p) Appendix B: Some Derivations Appendix C: Additional Data Sets References Index of Examples Index





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