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- catalog abstract ""This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative censoring and treatment assignment in so-called semiparametric models. Semiparametric models are particularly attractive since they allow the presence of large unmodeled nuisance parameters. These techniques include estimation of regression parameters in the familiar (multivariate) generalized linear regression and multiplicative intensity models. They go beyond standard statistical approaches by incorporating all the observed data to allow for informative censoring, to obtain maximal efficiency, and by developing estimators of causal effects. It can be used to teach masters and Ph. D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data."--Jacket.".
- catalog contributor b13071509.
- catalog contributor b13071510.
- catalog created "c2003.".
- catalog date "2003".
- catalog date "c2003.".
- catalog dateCopyrighted "c2003.".
- catalog description ""This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative censoring and treatment assignment in so-called semiparametric models. Semiparametric models are particularly attractive since they allow the presence of large unmodeled nuisance parameters. These techniques include estimation of regression parameters in the familiar (multivariate) generalized linear regression and multiplicative intensity models.".
- catalog description "Includes bibliographical references (p. 371-387) and indexes.".
- catalog description "Motivation, Bibliographic History, and an Overview of the book -- Tour through the General Estimation Problem -- Estimation in a high-dimensional full data model -- The curse of dimensionality in the full data model -- Coarsening at random -- The curse of dimensionality revisited -- The observed data model -- General method for construction of locally efficient estimators -- Comparison with maximum likelihood estimation -- Example: Causal Effect of Air Pollution on Short-Term Asthma Response -- Estimating Functions -- Orthogonal complement of a nuisance tangent space -- Review of efficiency theory -- Estimating functions -- Orthogonal complement of a nuisance tangent space in an observed data model -- Basic useful results to compute projections -- Robustness of Estimating Functions -- Robustness of estimating functions against misspecification of linear convex nuisance parameters -- Double robustness of observed data estimating functions -- Understanding double robustness for a general semiparametric model -- Doubly robust estimation in censored data models -- Using Cross-Validation to Select Nuisance Parameter Models -- A semiparametric model selection criterian -- Forward/backward selection of a nuisance parameter model based on cross-validation with respect to the parameter of interest -- Data analysis example: Estimating the causal relationship between boiled water use and diarrhea in HIV-positive men -- General Methodology -- Full Data Estimating Functions.".
- catalog description "They go beyond standard statistical approaches by incorporating all the observed data to allow for informative censoring, to obtain maximal efficiency, and by developing estimators of causal effects. It can be used to teach masters and Ph. D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data."--Jacket.".
- catalog extent "xii, 397 p. :".
- catalog identifier "0387955569 (alk. paper)".
- catalog isPartOf "Springer series in statistics".
- catalog issued "2003".
- catalog issued "c2003.".
- catalog language "eng".
- catalog publisher "New York : Springer,".
- catalog subject "519.5/4 21".
- catalog subject "Censored observations (Statistics)".
- catalog subject "Estimation theory.".
- catalog subject "Longitudinal Studies.".
- catalog subject "Longitudinal method.".
- catalog subject "Nonparametric statistics.".
- catalog subject "QA278.8 .L33 2003".
- catalog subject "Statistics, Nonparametric.".
- catalog tableOfContents "Motivation, Bibliographic History, and an Overview of the book -- Tour through the General Estimation Problem -- Estimation in a high-dimensional full data model -- The curse of dimensionality in the full data model -- Coarsening at random -- The curse of dimensionality revisited -- The observed data model -- General method for construction of locally efficient estimators -- Comparison with maximum likelihood estimation -- Example: Causal Effect of Air Pollution on Short-Term Asthma Response -- Estimating Functions -- Orthogonal complement of a nuisance tangent space -- Review of efficiency theory -- Estimating functions -- Orthogonal complement of a nuisance tangent space in an observed data model -- Basic useful results to compute projections -- Robustness of Estimating Functions -- Robustness of estimating functions against misspecification of linear convex nuisance parameters -- Double robustness of observed data estimating functions -- Understanding double robustness for a general semiparametric model -- Doubly robust estimation in censored data models -- Using Cross-Validation to Select Nuisance Parameter Models -- A semiparametric model selection criterian -- Forward/backward selection of a nuisance parameter model based on cross-validation with respect to the parameter of interest -- Data analysis example: Estimating the causal relationship between boiled water use and diarrhea in HIV-positive men -- General Methodology -- Full Data Estimating Functions.".
- catalog title "Unified methods for censored longitudinal data and causality / Mark J. van der Laan, James M. Robins.".
- catalog type "text".