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Statistical analysis of panel count ...

Sun, Jianguo, (1961-)

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Statistical analysis of panel count data /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Statistical analysis of panel count data // Jianguo Sun, Singqiu Zhao.
作者:	Sun, Jianguo,
其他作者:	Zhao, Xingqiu.
出版者:	New York :Springer Verlag, : c2013.,
面頁冊數:	xv, 271 p. :ill. ;23 cm.
標題:	Panel analysis. -
ISBN:	1461487145
ISSN:	14318776

Statistical analysis of panel count data /
Sun, Jianguo,1961-

Statistical analysis of panel count data /Jianguo Sun, Singqiu Zhao. - New York :Springer Verlag,c2013. - xv, 271 p. :ill. ;23 cm. - Statistics for biology and health,1431-8776. - Statistics for biology and health,.

Includes bibliographical references and index.

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.

ISBN: 1461487145EUR85.00

ISSN: 14318776

LCCN: 2013947164Subjects--Topical Terms:

565934
Panel analysis.

LC Class. No.: H61.26 / .S86 2013

Dewey Class. No.: 519.5

Statistical analysis of panel count data /
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505 0 # $t Introduction -- $t Poisson models and parameter inference -- $t Nonparametric estimation -- $t Nonparametric comparison of point processes -- $t Regression analysis of panel count data I -- $t Regression analysis of panel count data II -- $t Analysis of multivariate panel count data -- $t Other topics -- $t Some sets of data.
520 # $a 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.
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