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Semiparametric Estimation In Hazards Models With Censoring Indicators Missing At Random
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Book Synopsis Semiparametric Estimation in Hazards Models with Censoring Indicators Missing at Random by : Chunling Liu (Ph. D.)
Download or read book Semiparametric Estimation in Hazards Models with Censoring Indicators Missing at Random written by Chunling Liu (Ph. D.) and published by . This book was released on 2008 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Semiparametric Estimation in Hazards Models with Censoring Indicators Missing at Random by : Chunling Liu
Download or read book Semiparametric Estimation in Hazards Models with Censoring Indicators Missing at Random written by Chunling Liu and published by Open Dissertation Press. This book was released on 2017-01-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Semiparametric Estimation in Hazards Models With Censoring Indicators Missing at Random" by Chunling, Liu, 劉春玲, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b4020396 Subjects: Parameter estimation Regression analysis Competing risks
Book Synopsis Partial Linear Semi-parametric Additive Hazards Models for Randomly Censored Survival Time Data by : Chaofeng Liu
Download or read book Partial Linear Semi-parametric Additive Hazards Models for Randomly Censored Survival Time Data written by Chaofeng Liu and published by . This book was released on 2002 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimation of Regression Coefficients in the Competing Risks Model with Missing Cause of Failure by : Kaifeng Lu
Download or read book Estimation of Regression Coefficients in the Competing Risks Model with Missing Cause of Failure written by Kaifeng Lu and published by . This book was released on 2002 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: cause-specific hazard, doubly robust, imputation, influence function, inverse probability weighting, locally efficient, missing at random, partial likelihood, proportional hazards model, semiparametric model.
Book Synopsis Semiparametric Estimation and Variable Selection Under Length-biased Sampling with Heavy Censoring by : Omidali Aghababaei Jazi
Download or read book Semiparametric Estimation and Variable Selection Under Length-biased Sampling with Heavy Censoring written by Omidali Aghababaei Jazi and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Semiparametric estimation procedures under Cox proportional hazards model and length-biased sampling have been developed using the weighted estimating equation method and the likelihood-based approaches over the past decade \citep{shenetal2017}. The common feature of the procedures is that they are driven by risk sets just prior to failure times. Under length-biased sampling, however, censoring is informative and failing to incorporate the information on censored data into the estimation mechanismcan lead to a substantial loss of efficiency when length-biased data are subject to heavy censoring; i.e. more than 50\% of the data are censored. We compute the likelihood contribution for uncensored and censored data separately and propose maximum approximate partial likelihood estimation (MAPLE). The procedure is further improved by exploiting the additional information for uncensored data under length-biased sampling. We call this procedure maximum approximate composite partial likelihood estimation (C-MAPLE). The asymptotic properties of the estimator from C-MAPLE are established using the functional delta method. It is shown in a simulation study that C-MAPLE and MAPLE outperform other procedures under the Cox proportional hazards model and length-biased sampling with heavy censoring. We also apply the proposed procedures to the International Stroke Trial (IST) data collected in Argentina. We next develop a unified class of penalized estimating functions which encompasses any estimation procedure under the Cox proportional hazards model and length-biased sampling. We solve the penalized estimating function by slightly perturbing the penalty function in the Minorize-Maximization algorithm \citep{hunterli2005}.We then investigate the asymptotic properties of the penalized estimators. It is shown that the penalized estimators are $\sqrt n$-consistent and with a proper choice of the tuning parameter and the penalty function, they possess the same asymptotic properties as if the true model were known a priori which is termed as the oracle property. Two simulation studies are conducted to compare the performance of the penalized estimators and confirm our theoretical results. The procedure is also used for variable selection under the Cox proportional hazards model for the IST data collected in Argentina. We further study tuning parameter selections in the penalized estimating functions via generalized information criteria (GIC). We first demonstrate the asymptotic behaviour of the loss function under C-MAPLE and then investigate the consistency of the GIC.Finally, we use bias-adjusted risk set sampling to introduce the Schoenfeld residuals for length-biased data.We conduct a simulation study to illustrate the performance of the Schoenfeld-type residuals in verifying the proportionality assumption and highlighting the trend of nonproportionality"--
Book Synopsis Advances in Survival Analysis by : Narayanaswamy Balakrishnan
Download or read book Advances in Survival Analysis written by Narayanaswamy Balakrishnan and published by Elsevier. This book was released on 2004-01-30 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistics: Advances in Survival Analysis covers all important topics in the area of Survival Analysis. Each topic has been covered by one or more chapters written by internationally renowned experts. Each chapter provides a comprehensive and up-to-date review of the topic. Several new illustrative examples have been used to demonstrate the methodologies developed. The book also includes an exhaustive list of important references in the area of Survival Analysis. - Includes up-to-date reviews on many important topics - Chapters written by many internationally renowned experts - Some Chapters provide completely new methodologies and analyses - Includes some new data and methods of analyzing them
Book Synopsis Semiparametric Theory and Missing Data by : Anastasios Tsiatis
Download or read book Semiparametric Theory and Missing Data written by Anastasios Tsiatis and published by Springer Science & Business Media. This book was released on 2007-01-15 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.
Book Synopsis Semiparametric Estimators for the Regression Coefficients in the Linear Transformation Competing Risks Models with Missing Cause of Failure by : Guozhi Gao
Download or read book Semiparametric Estimators for the Regression Coefficients in the Linear Transformation Competing Risks Models with Missing Cause of Failure written by Guozhi Gao and published by . This book was released on 2005 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: Influence function, Multiple Imputation, Missing at random, Semiparametric estimator, Inverse probability weighted, Linear transformation model, Double Robustness, Competing risks, Cause-specific hazard.
Book Synopsis Semiparametric Estimators for the Regression Coefficients in the Linear Transformation Competing Risks Models with Missing Cause of Failure by :
Download or read book Semiparametric Estimators for the Regression Coefficients in the Linear Transformation Competing Risks Models with Missing Cause of Failure written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In many clinical studies, researchers are mainly interested in studying the effects of some prognostic factors on the hazard of failure from a specific cause while individuals may failure from multiple causes. This leads to a competing risks problem. Often, due to various reasons such as finite study duration, loss to follow-up, or withdrawal from the study, the time-to-failure is right-censored for some individuals. Although the proportional hazards model has been commonly used in analyzing survival data, there are circumstances where other models are more appropriate. Here we consider the class of linear transformation models that contains the proportional hazards model and the proportional odds model as special cases. Sometimes, patients are known to die but the cause of death is unavailable. It is well known that when cause of failure is missing, ignoring the observations with missing cause or treating them as censored may result in erroneous inferences. Under the Missing At Random assumption, we propose two methods to estimate the regression coefficients in the linear transformation models. The augmented inverse probability weighting method is highly efficient and doubly robust. In addition, it allows the possibility of using auxiliary covariates to model the missing mechanism. The multiple imputation method is very efficient, is straightforward and easy to implement and also allows for the use of auxiliary covariates. The asymptotic properties of these estimators are developed using theory of counting processes and semiparametric theory for missing data problems. Simulation studies demonstrate the relevance of the theory in finite samples. These methods are also illustrated using data from a breast cancer stage II clinical trial.
Book Synopsis Estimation Under Censoring with Missing Failure Indicators by : Sundarraman Subramanian
Download or read book Estimation Under Censoring with Missing Failure Indicators written by Sundarraman Subramanian and published by . This book was released on 1995 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Semiparametric Approach to Hazard Estimation with Randomly Right-censored Observations by : Djokouri Alexis Kouassi
Download or read book A Semiparametric Approach to Hazard Estimation with Randomly Right-censored Observations written by Djokouri Alexis Kouassi and published by . This book was released on 1991 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Semiparametric Estimation in Censored Regression Models by : Hui-Lin Lin
Download or read book Semiparametric Estimation in Censored Regression Models written by Hui-Lin Lin and published by . This book was released on 1991 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Frailty Model by : Luc Duchateau
Download or read book The Frailty Model written by Luc Duchateau and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.
Book Synopsis The Prevention and Treatment of Missing Data in Clinical Trials by : National Research Council
Download or read book The Prevention and Treatment of Missing Data in Clinical Trials written by National Research Council and published by National Academies Press. This book was released on 2010-12-21 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.
Book Synopsis Efficient Estimation of Missing Data Models Using Moment Conditions and Semiparametric Restrictions by : Bryan S. Graham
Download or read book Efficient Estimation of Missing Data Models Using Moment Conditions and Semiparametric Restrictions written by Bryan S. Graham and published by . This book was released on 2008 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper shows that the semiparametric efficiency bound for a parameter identified by an unconditional moment restriction with data missing at random (MAR) coincides with that of a particular augmented moment condition problem. The augmented system consists of the inverse probability weighted (IPW) original moment restriction and an additional conditional moment restriction which exhausts all other implications of the MAR assumption. The paper also investigates the value of additional semiparametric restrictions on the conditional expectation function (CEF) of the original moment function given always-observed covariates. In the missing outcome context, for example, such restrictions are implied by a semiparametric model for the outcome CEF given always-observed covariates. The efficiency bound associated with this model is shown to also coincide with that of a particular moment condition problem. Some implications of these results for estimation are briefly discussed.
Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu
Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Book Synopsis The Birnbaum-Saunders Distribution by : Victor Leiva
Download or read book The Birnbaum-Saunders Distribution written by Victor Leiva and published by Academic Press. This book was released on 2015-10-26 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Birnbaum-Saunders Distribution presents the statistical theory, methodology, and applications of the Birnbaum-Saunders distribution, a very flexible distribution for modeling different types of data (mainly lifetime data). The book describes the most recent theoretical developments of this model, including properties, transformations and related distributions, lifetime analysis, and shape analysis. It discusses methods of inference based on uncensored and censored data, goodness-of-fit tests, and random number generation algorithms for the Birnbaum-Saunders distribution, also presenting existing and future applications. - Introduces inference in the Birnbaum-Saunders distribution - Provides a comprehensive review of the statistical theory and methodology of the Birnbaum-Distribution - Discusses different applications of the Birnbaum-Saunders distribution - Explains characterization and the lifetime analysis
