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Probability, Statistics and Modelling in Public Health


Probability, Statistics and Modelling in Public Health



von: M.S. Nikulin, Daniel Commenges, Catherine Huber-Carol

213,99 €

Verlag: Springer
Format: PDF
Veröffentl.: 10.02.2006
ISBN/EAN: 9780387260235
Sprache: englisch
Anzahl Seiten: 479

Dieses eBook enthält ein Wasserzeichen.

Beschreibungen

<STRONG>Probability, Statistics and Modelling in Public Health</STRONG> consists of refereed contributions by expert biostatisticians that discuss various probabilistic and statistical models used in public health. Many of them are based on the work of Marvin Zelen of the Harvard School of Public Health. Topics discussed include models based on Markov and semi-Markov processes, multi-state models, models and methods in lifetime data analysis, accelerated failure models, design and analysis of clinical trials, Bayesian methods, pharmaceutical and environmental statistics, degradation models, epidemiological methods, screening programs, early detection of diseases, and measurement and analysis of quality of life.
Forward and Backward Recurrence Times and Length Biased Sampling: Age Specific Models.- Difference between Male and Female Cancer Incidence Rates: How Can It Be Explained?.- Non-parametric estimation in degradation-renewal-failure models.- The Impact of Dementia and Sex on the Disablement in the Elderly.- Nonparametric Estimation for Failure Rate Functions of Discrete Time semi-Markov Processes.- Some recent results on joint degradation and failure time modeling.- Estimation in a Markov chain regression model with missing covariates.- Tests of Fit based on Products of Spacings.- A Survival Model With Change-Point in Both Hazard and Regression Parameters.- Mortality in Varying Environment.- Goodness of Fit of a joint model for event time and nonignorable missing Longitudinal Quality of Life data.- Three approaches for estimating prevalence of cancer with reversibility. Application to colorectal cancer.- On statistics of inverse gamma process as a model of wear.- Operating Characteristics of Partial Least Squares in Right-Censored Data Analysis and Its Application in Predicting the Change of HIV-I RNA.- Inference for a general semi-Markov model and a sub-model for independent competing risks.- Estimation Of Density For Arbitrarily Censored And Truncated Data.- Statistical Analysis of Some Parametric Degradation Models.- Use of statistical modelling methods in clinical practice.- Degradation-Threshold-Shock Models.- Comparisons of Test Statistics Arising from Marginal Analyses of Multivariate Survival Data.- Nonparametric Estimation and Testing in Survival Models.- Selecting a semi-parametric estimator by the expected log-likelihood.- Imputing responses that are not missing.- Bivariate Decision Processes.- Weighted Logrank Tests With Multiple Events.- Explained Variation and Predictive Accuracy in General Parametric Statistical Models: The Role of Model Misspecification.- Optimization of Breast Cancer Screening Modalities.- Sequential Analysis of Quality of Life Rasch Measurements.- Three Types of Hazard Functions Curves Described.- On the Analysis of Fuzzy Life Times and Quality of Life Data.- Statistical Inference for Two-Sample and Regression Models with Heterogeneity Effect: A Collected-Sample Perspective.- Failure Distributions Associated With General Compound Renewal Damage Processes.
<P><STRONG>Probability, Statistics and Modelling in Public Health</STRONG> consists of refereed contributions by expert biostatisticians that discuss various probabilistic and statistical models used in public health. Many of them are based on the work of Marvin Zelen of the Harvard School of Public Health. Topics discussed include models based on Markov and semi-Markov processes, multi-state models, models and methods in lifetime data analysis, accelerated failure models, design and analysis of clinical trials, Bayesian methods, pharmaceutical and environmental statistics, degradation models, epidemiological methods, screening programs, early detection of diseases, and measurement and analysis of quality of life. </P>
<P><EM>Audience</EM></P>
<P>This book is intended for researchers interested in statistical methodology in the biomedical field. </P>
Marks the advances of statistical methods in public health Includes supplementary material: sn.pub/extras

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