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© 2013

Statistical Analysis of Panel Count Data

Book

Part of the Statistics for Biology and Health book series (SBH, volume 80)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Jianguo Sun, Xingqiu Zhao
    Pages 1-22
  3. Jianguo Sun, Xingqiu Zhao
    Pages 23-45
  4. Jianguo Sun, Xingqiu Zhao
    Pages 47-70
  5. Jianguo Sun, Xingqiu Zhao
    Pages 71-90
  6. Jianguo Sun, Xingqiu Zhao
    Pages 91-120
  7. Jianguo Sun, Xingqiu Zhao
    Pages 121-153
  8. Jianguo Sun, Xingqiu Zhao
    Pages 155-187
  9. Jianguo Sun, Xingqiu Zhao
    Pages 189-222
  10. Jianguo Sun, Xingqiu Zhao
    Pages 223-251
  11. Back Matter
    Pages 253-271

About this book

Introduction

Panel count data occur in studies that concern recurrent events, or event history studies, when study subjects are observed only at discrete time points.  By recurrent events, we mean the event that can occur or happen multiple times or repeatedly. Examples of recurrent events include disease infections, hospitalizations in medical studies, warranty claims of automobiles or system break-downs in reliability studies.  In fact, many other fields yield event history data too such as demographic studies, economic studies and social sciences.  For the cases where the study subjects are observed continuously, the resulting data  are usually referred to as recurrent event data.

This book collects and unifies statistical models and methods that have been developed for analyzing panel count data.  It provides the first comprehensive coverage of the topic. The main focus is on methodology, but for the benefit of the reader, the applications of the methods to real data are also discussed along with numerical calculations. There exists a great deal of literature on the analysis of recurrent event data. This book fills the void in the literature on the analysis of panel count data.

This book provides an up-to-date reference for scientists who are conducting research on the analysis of panel count data. It will also be instructional for those who need to analyze panel count data to answer substantive research questions.  In addition, it can be used as a text for a graduate course in statistics or biostatistics that assumes a basic knowledge of probability and statistics. 

Keywords

Biostatistics Nonparametric estimation Panel Count Data Parametric inference Point processes Poisson models Recurrent Event Data Regression Analysis

Authors and affiliations

  1. 1.Department of StatisticsUniversity of MissouriColumbiaUSA
  2. 2.Department of Applied MathematicsThe Hong Kong Polytechnic UniversityHong KongHong Kong SAR

About the authors

Jianguo (Tony) Sun is a professor at the Department of Statistics of the University of Missouri.  He obtained his Ph.D. at the University of Waterloo and has been developing novel statistical methods for the analysis of interval-censored failure time data and panel count data over the last 20 years.  In particular, he published "The Statistical Analysis of Interval-censored Failure Time Data" (Springer, 2006), the first book on interval-censored data.  He also co-authored with Drs. Chen and Peace the volume "Interval-censored Time-to-Event Data: Methods and Applications" (Chapman and Hall, 2012).

Xingqiu Zhao is a faculty member of The Hong Kong Polytechnic University and she obtained her Ph.D. at McMaster University.  Her research interests include econometrics, financial mathematics, longitudinal data analysis, stochastic process models and applications, survival analysis, and time series analysis.  In particular, she has published many papers on new statistical inference procedures for analyzing interval-censored failure time data, recurrent event data and panel count data.

Bibliographic information

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Reviews

From the reviews:

“The book under review presents on a total of 271 pages an introduction into the methodology of analysing panel count data. It addresses to scientists and graduate students with basic knowledge about probability theory and statistics. … the book under review is recommended to researchers with strong background of probability and statistics interested in methodology on panel count data.” (Iris Burkholder, zbMATH, Vol. 1282, 2014)