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Author: Adrian Colin Cameron
Publisher: Cambridge University Press
ISBN: 1107014166
Category : Business & Economics
Languages : en
Pages : 597
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Book Description
This book provides the most comprehensive and up-to-date account of regression methods to explain the frequency of events.
Author: Adrian Colin Cameron
Publisher: Cambridge University Press
ISBN: 1107014166
Category : Business & Economics
Languages : en
Pages : 597
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Book Description
This book provides the most comprehensive and up-to-date account of regression methods to explain the frequency of events.
Author: Joseph M. Hilbe
Publisher: Cambridge University Press
ISBN: 1107028337
Category : Business & Economics
Languages : en
Pages : 301
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Book Description
This book provides guidelines and fully worked examples of how to select, construct, interpret and evaluate the full range of count models.
Author: A. Colin Cameron
Publisher: Cambridge University Press
ISBN: 9780521635677
Category : Business & Economics
Languages : en
Pages : 436
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Book Description
This analysis provides a comprehensive account of models and methods to interpret frequency data.
Author: Jianguo Sun
Publisher: Springer Science & Business Media
ISBN: 1461487153
Category : Medical
Languages : en
Pages : 283
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Book Description
Panel count data occur in studies that concern recurrent events, or event history studies, when study subjects are observed only at discrete time points. By recurrent events, we mean the event that can occur or happen multiple times or repeatedly. Examples of recurrent events include disease infections, hospitalizations in medical studies, warranty claims of automobiles or system break-downs in reliability studies. In fact, many other fields yield event history data too such as demographic studies, economic studies and social sciences. For the cases where the study subjects are observed continuously, the resulting data are usually referred to as recurrent event data. This book collects and unifies statistical models and methods that have been developed for analyzing panel count data. It provides the first comprehensive coverage of the topic. The main focus is on methodology, but for the benefit of the reader, the applications of the methods to real data are also discussed along with numerical calculations. There exists a great deal of literature on the analysis of recurrent event data. This book fills the void in the literature on the analysis of panel count data. This book provides an up-to-date reference for scientists who are conducting research on the analysis of panel count data. It will also be instructional for those who need to analyze panel count data to answer substantive research questions. In addition, it can be used as a text for a graduate course in statistics or biostatistics that assumes a basic knowledge of probability and statistics.
Author: Joseph M. Hilbe
Publisher: Cambridge University Press
ISBN: 1139500066
Category : Mathematics
Languages : en
Pages : 573
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Book Description
This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation and evaluation. Complete Stata and R codes are provided throughout the text, with additional code (plus SAS), derivations and data provided on the book's website. Written for the practising researcher, the text begins with an examination of risk and rate ratios, and of the estimating algorithms used to model count data. The book then gives an in-depth analysis of Poisson regression and an evaluation of the meaning and nature of overdispersion, followed by a comprehensive analysis of the negative binomial distribution and of its parameterizations into various models for evaluating count data.
Author: Rainer Winkelmann
Publisher: Springer Science & Business Media
ISBN: 366221735X
Category : Business & Economics
Languages : en
Pages : 223
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Book Description
This book presents statistical methods for the analysis of events. The primary focus is on single equation cross section models. The book addresses both the methodology and the practice of the subject and it provides both a synthesis of a diverse body of literature that hitherto was available largely in pieces, as well as a contribution to the progress of the methodology, establishing several new results and introducing new models. Starting from the standard Poisson regression model as a benchmark, the causes, symptoms and consequences of misspecification are worked out. Both parametric and semi-parametric alternatives are discussed. While semi-parametric models allow for robust interference, parametric models can identify features of the underlying data generation process.
Author: Gerhard Tutz
Publisher: Cambridge University Press
ISBN: 1139499580
Category : Mathematics
Languages : en
Pages : 573
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Book Description
This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods. The book is accompanied by an R package that contains data sets and code for all the examples.
Author: Jason W. Osborne
Publisher: SAGE Publications
ISBN: 1506302750
Category : Psychology
Languages : en
Pages : 489
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Book Description
In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.
Author: John P. Hoffmann
Publisher: Univ of California Press
ISBN: 0520289293
Category : Mathematics
Languages : en
Pages : 428
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Book Description
Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. Instead, they must measure and analyze these events and phenomena in a discrete manner. This book provides an introduction and overview of several statistical models designed for these types of outcomes—all presented with the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis. Numerous examples from the social sciences demonstrate the practical applications of these models. The chapters address logistic and probit models, including those designed for ordinal and nominal variables, regular and zero-inflated Poisson and negative binomial models, event history models, models for longitudinal data, multilevel models, and data reduction techniques such as principal components and factor analysis. Each chapter discusses how to utilize the models and test their assumptions with the statistical software Stata, and also includes exercise sets so readers can practice using these techniques. Appendices show how to estimate the models in SAS, SPSS, and R; provide a review of regression assumptions using simulations; and discuss missing data. A companion website includes downloadable versions of all the data sets used in the book.
Author: J. Scott Long
Publisher: SAGE
ISBN: 9780803973749
Category : Mathematics
Languages : en
Pages : 334
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Book Description
Evaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common methods of derivation, interpretation, and testing. The author also explains how models relate to linear regression models whenever possible. Annotation c.
