Structurally Dependent Competing Risks
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Applied Econometrics
| Author | : Chia-Lin Chang |
| Publisher | : MDPI |
| Total Pages | : 222 |
| Release | : 2019-05-13 |
| Genre | : Business & Economics |
| ISBN | : 3038979260 |
Although the theme of the monograph is primarily related to “Applied Econometrics”, there are several theoretical contributions that are associated with empirical examples, or directions in which the novel theoretical ideas might be applied. The monograph is associated with significant and novel contributions in theoretical and applied econometrics; economics; theoretical and applied financial econometrics; quantitative finance; risk; financial modeling; portfolio management; optimal hedging strategies; theoretical and applied statistics; applied time series analysis; forecasting; applied mathematics; energy economics; energy finance; tourism research; tourism finance; agricultural economics; informatics; data mining; bibliometrics; and international rankings of journals and academics.
Progressive Censoring
| Author | : N. Balakrishnan |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 255 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461213347 |
This new book offers a guide to the theory and methods of progressive censoring. In many industrial experiments involving lifetimes of machines or units, experiments have to be terminated early. Progressive Censoring first introduces progressive sampling foundations, and then discusses various properties of progressive samples. The book points out the greater efficiency gained by using this scheme instead of classical right-censoring methods.
Longitudinal Research with Latent Variables
| Author | : Kees van Montfort |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 311 |
| Release | : 2010-05-17 |
| Genre | : Mathematics |
| ISBN | : 3642117600 |
Since Charles Spearman published his seminal paper on factor analysis in 1904 and Karl Joresk ̈ og replaced the observed variables in an econometric structural equation model by latent factors in 1970, causal modelling by means of latent variables has become the standard in the social and behavioural sciences. Indeed, the central va- ables that social and behavioural theories deal with, can hardly ever be identi?ed as observed variables. Statistical modelling has to take account of measurement - rors and invalidities in the observed variables and so address the underlying latent variables. Moreover, during the past decades it has been widely agreed on that serious causal modelling should be based on longitudinal data. It is especially in the ?eld of longitudinal research and analysis, including panel research, that progress has been made in recent years. Many comprehensive panel data sets as, for example, on human development and voting behaviour have become available for analysis. The number of publications based on longitudinal data has increased immensely. Papers with causal claims based on cross-sectional data only experience rejection just for that reason.
Joint Models for Longitudinal and Time-to-Event Data
| Author | : Dimitris Rizopoulos |
| Publisher | : CRC Press |
| Total Pages | : 279 |
| Release | : 2012-06-22 |
| Genre | : Mathematics |
| ISBN | : 1439872864 |
In longitudinal studies it is often of interest to investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest, e.g., prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment of random effects joint models for longitudinal and time-to-event outcomes that can be utilized to analyze such data. The content is primarily explanatory, focusing on applications of joint modeling, but sufficient mathematical details are provided to facilitate understanding of the key features of these models. All illustrations put forward can be implemented in the R programming language via the freely available package JM written by the author. All the R code used in the book is available at: http://jmr.r-forge.r-project.org/
Quality and Reliability Management and Its Applications
| Author | : Hoang Pham |
| Publisher | : Springer |
| Total Pages | : 453 |
| Release | : 2015-11-20 |
| Genre | : Technology & Engineering |
| ISBN | : 1447167783 |
Integrating development processes, policies, and reliability predictions from the beginning of the product development lifecycle to ensure high levels of product performance and safety, this book helps companies overcome the challenges posed by increasingly complex systems in today’s competitive marketplace. Examining both research on and practical aspects of product quality and reliability management with an emphasis on applications, the book features contributions written by active researchers and/or experienced practitioners in the field, so as to effectively bridge the gap between theory and practice and address new research challenges in reliability and quality management in practice. Postgraduates, researchers and practitioners in the areas of reliability engineering and management, amongst others, will find the book to offer a state-of-the-art survey of quality and reliability management and practices.
Survival Analysis
| Author | : Xian Liu |
| Publisher | : John Wiley & Sons |
| Total Pages | : 433 |
| Release | : 2012-06-13 |
| Genre | : Mathematics |
| ISBN | : 1118307674 |
Survival analysis concerns sequential occurrences of events governed by probabilistic laws. Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis. Assumes only a minimal knowledge of SAS whilst enabling more experienced users to learn new techniques of data input and manipulation. Provides numerous examples of SAS code to illustrate each of the methods, along with step-by-step instructions to perform each technique. Highlights the strengths and limitations of each technique covered. Covering a wide scope of survival techniques and methods, from the introductory to the advanced, this book can be used as a useful reference book for planners, researchers, and professors who are working in settings involving various lifetime events. Scientists interested in survival analysis should find it a useful guidebook for the incorporation of survival data and methods into their projects.
Competing Risk Analysis of Japan's Small Financial Institutions
| Author | : Xinghua Yu |
| Publisher | : |
| Total Pages | : 58 |
| Release | : 2006 |
| Genre | : Bank failures |
| ISBN | : |
This paper develops a dependent competing risks model to investigate the determinants of time to bankruptcy and time to merger jointly, and more importantly, to investigate their interdependence. This paper identifies strong interdependence between the bankruptcy and merger hazards, both through the correlation of the unobserved heterogeneities and through the preventive behavior of the individual firms. This paper shows that the common practice of assuming the independence of the competing risks would yield biased estimates and lower the predictive accuracy. In addition, this paper addresses important econometric-theoretic questions that arise with the empirical analysis, namely, identification and testing a hypothesis in a nonstandard situation.--Author's abstract.
Analysing Survival Data from Clinical Trials and Observational Studies
| Author | : Ettore Marubini |
| Publisher | : John Wiley & Sons |
| Total Pages | : 436 |
| Release | : 2004-07-02 |
| Genre | : Mathematics |
| ISBN | : 9780470093412 |
A practical guide to methods of survival analysis for medical researchers with limited statistical experience. Methods and techniques described range from descriptive and exploratory analysis to multivariate regression methods. Uses illustrative data from actual clinical trials and observational studies to describe methods of analysing and reporting results. Also reviews the features and performance of statistical software available for applying the methods of analysis discussed.
