The Analysis of Current Status Data on Point Processes

This article considers the analysis of event count data in which each subject is observed at only one time point and no information is available on subjects between their entry time and observation points. This type of data, often referred to as current status data, arises frequently-for example, in...

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Bibliographic Details
Published inJournal of the American Statistical Association Vol. 88; no. 424; pp. 1449 - 1454
Main Authors Sun, Jianguo, Kalbfleisch, John D.
Format Journal Article
LanguageEnglish
Published Alexandria, VA Taylor & Francis Group 01.12.1993
American Statistical Association
Taylor & Francis Ltd
Subjects
Applications
Biology, psychology, social sciences
Comparison test
Demography
Estimators
Exact sciences and technology
Gaussian distributions
Insurance, economics, finance
Isotonic regression
Logical givens
Mathematics
Medical sciences
Poisson process
Probabilities
Probability and statistics
Random variables
Reliability, life testing, quality control
Sciences and techniques of general use
Statistical inferences
Statistical theories
Statistics
Theory and Methods
Tumorgenicity study
Tumors
Comparison test
Data analysis
Tumorigenicity
Point process
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ISSN0162-1459
1537-274X
DOI10.1080/01621459.1993.10476432

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Summary:This article considers the analysis of event count data in which each subject is observed at only one time point and no information is available on subjects between their entry time and observation points. This type of data, often referred to as current status data, arises frequently-for example, in demography, epidemiology, and reliability studies. Statistical methods for the analysis of current status data from point processes are proposed. Specifically, a statistic for testing the equality of the mean functions of point processes is presented and its asymptotic distribution obtained. For illustration, the proposed method is used to analyze multiple tumor data from a tumorgenicity experiment, with focus on the comparison of tumor growth rates in male and female rats. The adequacy of the asymptotic distribution of the test statistic is evaluated in a small simulation study. Power comparisons with the usual parametric model are also obtained. Finally, some possible directions for further research are discussed.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0162-1459
1537-274X
DOI:10.1080/01621459.1993.10476432