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Case Studies in Bayesian Statistics : Volume V

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Cover of 'Case Studies in Bayesian Statistics : Volume V'

Table of Contents

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    Book Overview
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    Chapter 1 School Choice in NY City: A Bayesian Analysis of an Imperfect Randomized Experiment
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    Chapter 2 Adaptive Bayesian Designs for Dose-Ranging Drug Trials
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    Chapter 3 Modeling the Impact of Traffic-Related Air Pollution on Childhood Respiratory Illness
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    Chapter 4 A Hierarchical Model for Estimating Distribution Profiles of Soil Texture
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    Chapter 5 Assessing the Homogeneity of Three Odds Ratios: A Case Study in Small-Sample Inference
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    Chapter 6 Modeling Rates of Bone Growth and Loss Using Order-Restricted Inference and Stochastic Change Points
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    Chapter 7 Estimating Genotype Probabilities in Complex Pedigrees
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    Chapter 8 Identifying Carriers of a Genetic Modifier Using Nonparametric Bayesian Methods
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    Chapter 9 Bayesian Tools for EDA and Model Building: A Brainy Study
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    Chapter 10 Bayesian Protein Structure Prediction
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    Chapter 11 Bayesian Analysis of Sensory Inputs of a Mobile Robot
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    Chapter 12 Hidden Markov Models for Analysis of Biological Rhythm Data
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    Chapter 13 Using Prior Opinions to Examine Sample Size in Two Clinical Trials
Attention for Chapter 8: Identifying Carriers of a Genetic Modifier Using Nonparametric Bayesian Methods
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Chapter title
Identifying Carriers of a Genetic Modifier Using Nonparametric Bayesian Methods
Chapter number 8
Book title
Case Studies in Bayesian Statistics
Published by
Springer, New York, NY, January 2002
DOI 10.1007/978-1-4613-0035-9_8
Book ISBNs
978-0-387-95169-0, 978-1-4613-0035-9
Authors

Peter D. Hoff, Richard B. Halberg, Alexandra Shedlovsky, William F. Dove, Michael A. Newton, Hoff, Peter D., Halberg, Richard B., Shedlovsky, Alexandra, Dove, William F., Newton, Michael A.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 100%
Readers by discipline Count As %
Mathematics 1 100%

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