Statistical Methods for Overdispersed Count Data

Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages that allow their implementation. All methods are illustrated on datasets arising in the field of health economics. As several tools have been developed to tackle over-dispersed and zero-inflated data (such as adjustment methods and zero-inflated models), this book covers the topic in a comprehensive and interesting manner. Includes reading on several levels, including methodology and applications Presents the state-of-the-art on the most recent zero-inflated regression models Contains a single dataset that is used as a common thread for illustrating all methodologies Includes R code that allows the reader to apply methodologies

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  • Author : Jean-Francois Dupuy
  • Publisher : Elsevier
  • Pages : 192 pages
  • ISBN : 008102374X
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKStatistical Methods for Overdispersed Count Data

Statistical Methods for Overdispersed Count Data

Statistical Methods for Overdispersed Count Data
  • Author : Jean-Francois Dupuy
  • Publisher : Elsevier
  • Release : 19 November 2018
GET THIS BOOKStatistical Methods for Overdispersed Count Data

Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages that allow their implementation. All methods are illustrated on datasets arising in the field of health economics. As several tools have been developed to tackle over-dispersed and zero-inflated data (such as adjustment methods and zero-inflated models), this book covers the topic in a comprehensive and interesting manner. Includes reading on several levels, including

A Comparison of Statistical Models for Correlated Over-dispersed Count Data

A Comparison of Statistical Models for Correlated Over-dispersed Count Data
  • Author : Elizabeth Anne Wynn
  • Publisher : Unknown Publisher
  • Release : 22 January 2022
GET THIS BOOKA Comparison of Statistical Models for Correlated Over-dispersed Count Data

As the cost of RNA-sequencing (RNA-Seq) decreases, it becomes increasingly feasible to collect RNA-Seq data under complex study designs, including paired, longitudinal, and other correlated designs. Commonly used RNA-Seq analysis tools do not allow for correlation between observations, which is common in these types of studies. When applying statistical methods with mechanisms to account for correlated data to RNA-Seq experiments, extra considerations must be made because RNA-Seq experiments include data on 10,000 to 20,000 genes, resulting in a large number of statistical

Handbook of Statistical Methods for Randomized Controlled Trials

Handbook of Statistical Methods for Randomized Controlled Trials
  • Author : KyungMann Kim,Frank Bretz,Ying Kuen K. Cheung,Lisa V. Hampson
  • Publisher : CRC Press
  • Release : 23 August 2021
GET THIS BOOKHandbook of Statistical Methods for Randomized Controlled Trials

Statistical concepts provide scientific framework in experimental studies, including randomized controlled trials. In order to design, monitor, analyze and draw conclusions scientifically from such clinical trials, clinical investigators and statisticians should have a firm grasp of the requisite statistical concepts. The Handbook of Statistical Methods for Randomized Controlled Trials presents these statistical concepts in a logical sequence from beginning to end and can be used as a textbook in a course or as a reference on statistical methods for randomized

Analysis of Longitudinal Data with Example

Analysis of Longitudinal Data with Example
  • Author : You-Gan Wang,Liya Fu,Sudhir Paul
  • Publisher : CRC Press
  • Release : 28 January 2022
GET THIS BOOKAnalysis of Longitudinal Data with Example

Development in methodology on longitudinal data is fast. Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians to the updated methods on correlated data inference. This book will present a discussion of the modern approaches to inference, including the links between the theories of estimators and various types of efficient statistical models including likelihood-based approaches. The theory will be supported with practical examples of R-codes and R-packages applied to interesting case-studies from a

Introduction to Statistical Methods for Biosurveillance

Introduction to Statistical Methods for Biosurveillance
  • Author : Ronald D. Fricker
  • Publisher : Cambridge University Press
  • Release : 25 February 2013
GET THIS BOOKIntroduction to Statistical Methods for Biosurveillance

Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation,

Statistical Methods for Time-conditional Survival Probability and Equally Spaced Count Data

Statistical Methods for Time-conditional Survival Probability and Equally Spaced Count Data
  • Author : Victoria A. Gamerman
  • Publisher : Unknown Publisher
  • Release : 22 January 2022
GET THIS BOOKStatistical Methods for Time-conditional Survival Probability and Equally Spaced Count Data

This dissertation develops statistical methods for time-conditional survival probability and for equally spaced count data. Time-conditional survival probabilities are an alternative measure of future survival by accounting for time elapsed from diagnosis and are estimated as a ratio of survival probabilities. In Chapter 2, we derive the asymptotic distribution of a vector of nonparametric estimators and use weighted least squares methodology for the analysis of time-conditional survival probabilities. We show that the proposed test statistics for evaluating the relationship between time-conditional

Essential Statistical Methods for Medical Statistics

Essential Statistical Methods for Medical Statistics
  • Author : J. Philip Miller
  • Publisher : Elsevier
  • Release : 08 November 2010
GET THIS BOOKEssential Statistical Methods for Medical Statistics

Essential Statistical Methods for Medical Statistics presents only key contributions which have been selected from the volume in the Handbook of Statistics: Medical Statistics, Volume 27 (2009). While the use of statistics in these fields has a long and rich history, the explosive growth of science in general, and of clinical and epidemiological sciences in particular, has led to the development of new methods and innovative adaptations of standard methods. This volume is appropriately focused for individuals working in these fields. Contributors

Statistical Methods for Environmental Epidemiology with R

Statistical Methods for Environmental Epidemiology with R
  • Author : Roger D. Peng,Francesca Dominici
  • Publisher : Springer Science & Business Media
  • Release : 15 December 2008
GET THIS BOOKStatistical Methods for Environmental Epidemiology with R

As an area of statistical application, environmental epidemiology and more speci cally, the estimation of health risk associated with the exposure to - vironmental agents, has led to the development of several statistical methods and software that can then be applied to other scienti c areas. The stat- tical analyses aimed at addressing questions in environmental epidemiology have the following characteristics. Often the signal-to-noise ratio in the data is low and the targets of inference are inherently small risks. These

Statistical and Econometric Methods for Transportation Data Analysis

Statistical and Econometric Methods for Transportation Data Analysis
  • Author : Simon Washington,Matthew G. Karlaftis,Fred Mannering,Panagiotis Anastasopoulos
  • Publisher : CRC Press
  • Release : 30 January 2020
GET THIS BOOKStatistical and Econometric Methods for Transportation Data Analysis

Praise for the Second Edition: The second edition introduces an especially broad set of statistical methods ... As a lecturer in both transportation and marketing research, I find this book an excellent textbook for advanced undergraduate, Master’s and Ph.D. students, covering topics from simple descriptive statistics to complex Bayesian models. ... It is one of the few books that cover an extensive set of statistical methods needed for data analysis in transportation. The book offers a wealth of examples from

Statistical and Econometric Methods for Transportation Data Analysis, Second Edition

Statistical and Econometric Methods for Transportation Data Analysis, Second Edition
  • Author : Simon P. Washington,Matthew G. Karlaftis,Fred Mannering
  • Publisher : CRC Press
  • Release : 02 December 2010
GET THIS BOOKStatistical and Econometric Methods for Transportation Data Analysis, Second Edition

The complexity, diversity, and random nature of transportation problems necessitates a broad analytical toolbox. Describing tools commonly used in the field, Statistical and Econometric Methods for Transportation Data Analysis, Second Edition provides an understanding of a broad range of analytical tools required to solve transportation problems. It includes a wide breadth of examples and case studies covering applications in various aspects of transportation planning, engineering, safety, and economics. After a solid refresher on statistical fundamentals, the book focuses on continuous

Modern Statistical Methods for Spatial and Multivariate Data

Modern Statistical Methods for Spatial and Multivariate Data
  • Author : Norou Diawara
  • Publisher : Springer
  • Release : 29 June 2019
GET THIS BOOKModern Statistical Methods for Spatial and Multivariate Data

This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for

Bayesian Hierarchical Models

Bayesian Hierarchical Models
  • Author : Peter D. Congdon
  • Publisher : CRC Press
  • Release : 16 September 2019
GET THIS BOOKBayesian Hierarchical Models

An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling

Fundamental Statistical Methods for Analysis of Alzheimer's and Other Neurodegenerative Diseases

Fundamental Statistical Methods for Analysis of Alzheimer's and Other Neurodegenerative Diseases
  • Author : Katherine E. Irimata,Brittany N. Dugger,Jeffrey R. Wilson
  • Publisher : Johns Hopkins University Press
  • Release : 05 May 2020
GET THIS BOOKFundamental Statistical Methods for Analysis of Alzheimer's and Other Neurodegenerative Diseases

Allowing more people to aid in analyzing data—while promoting constructive dialogues with statisticians—this book will hopefully play an important part in unlocking the secrets of these confounding diseases.