Rational Choice Theory And Largescale Data Analysis

The relationship between rational choice theory and large-scale data analysis has become an important issue for sociologists. Though rational choice theory is well established in both sociology and economics, its influence on quantitative empirical sociology has been surprisingly limited. This book examines why there is hardly a link between the t

Politics & Social Sciences

Blossfeld, Hans-Peter

Prein, Gerald

Social Sciences

Routledge

The New Role Of Women: Family Formation In Modern Societies

Kiernan, Kathleen

Parenting & Relationships

Event History Analysis

Serving as both a student textbook and a professional reference/handbook, this volume explores the statistical methods of examining time intervals between successive state transitions or events. Examples include: survival rates of patients in medical studies, unemployment periods in economic studies, or the period of time it takes a criminal to break the law after his release in a criminological study. The authors illustrate the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data to the specific questions of data organization, to the concrete application of available program packages and the interpretation of the obtained results. Event History Analysis: * makes didactically accessible the inclusion of covariates in semi-parametric and parametric regression models based upon concrete examples * presents the unabbreviated close relationship underlying statistical theory * details parameter-free methods of analysis of event-history data and the possibilities of their graphical presentation * discusses specific problems of multi-state and multi-episode models * introduces time-varying covariates and the question of unobserved population heterogeneity * demonstrates, through examples, how to implement hypotheses tests and how to choose the right model.

Event History Analysis: Statistical theory and Application in the Social Sciences

Health, Fitness & Dieting

Hamerle, Alfred

Mayer, Karl Ulrich

Psychology & Counseling

Lawrence Erlbaum Associates, Inc.

Techniques of Event History Modeling: New Approaches To Causal Analysis

This volume is a companion and update to Event History Analysis and substantially extends the practical application of event history analysis. It also adds several important new models and concepts which have been developed in an extremely active research area since the late 1980s. It provides a comprehensive introductory account of event history modeling techniques and their usefulness for causal analysis in the social sciences. By giving many concrete application examples, it demonstrates that event history models allow a natural time-related representation of causal arguments in empirical studies. In contrast to structural equation analysis, which is based upon the observation of states and on "time-less" models, event history analysis employs the time-path of changes in states and relates changes in (qualitative and metric) causal variables in the past to changes in discrete outcomes in the future. Since effects follow their causes in time, this necessarily implies a temporal interval which may be very short or very long, but can never be zero or infinity. This book demonstrates that event history modeling is a major step forward in causal analysis because it is the most appropriate of all currently available methodologies to uncover such (normally unknown) lags between causes and their effects and reveals the various temporal shapes of the unfolding effect. This is because the transition rate can be used to represent the quantity of the causal effect at any point in time. A particular strength of this book lies in the description of a new approach to interdependent dynamical systems. It is shown that a causal approach to interdependent systems is easily possible with the help of the transition rate concept, and that the systems view is not a substitute for a proper causal approach in the social sciences.   This book also proposes that the social sciences should give up their traditional deterministic approach in empirical analyses in favor of a probabilistic one. It is argued that randomness should not only be seen as a technical term (arising because of limited empirical observation), but must be understood as a theoretical category; it is the propensity of social agents to change their behavior in the future under certain conditions that have taken place in the past and present. This means that the aim of statistical (and substantive) models must be to capture common elements in the behavior of people, or patterns of action that recur in many cases. In event history models, the causal effect to be explained is therefore the probability of a time-related change. Finally, the book is critical with regard to the widely applied models with unobserved heterogeneity since there is, in general, no way to make reliable assumptions about what has not been observed. Thus, in using such models, most empirical researchers try to draw sharp conclusions, even when these can only be generated by imposing much stronger assumptions than can be plausibly defended.   This book introduces the reader to the computer program TDA (Transition Data Analysis). Designed by Götz Rohwer, TDA estimates the kinds of models most frequently used with longitudinal data, in particular, event history data. The guiding principle in constructing TDA was the desire to make a broad range of event history analysis techniques as simple and convenient to apply as possible. TDA is now widely used in many research and university centers which analyze longitudinal data in Europe and the USA. It can be run on DOS-based personal computers and UNIX workstations. Included with this book is a disk with an executable version of the TDA program package for DOS-based machines, a file with the data used in the examples throughout the book, and a series of files containing the TDA set-ups for the examples. Thus, the reader is offered the unique opportunity to easily run and modify all the application examples on the computer. The authors have emphasized the strengths and weaknesses of event history modeling techniques in each example. In particular, they have complemented each practical application with a short exposition of the underlying statistical concepts. The examples start with an introduction to the background for the specific model. Then there is a demonstration of how to organize the input data and use the commands to control the TDA operation. Finally, a substantive interpretation of the obtained results is given.

Rohwer, G”tz

Psychology Press

This volume is a companion and update to Event History Analysis and substantially extends the practical application of event history analysis. It also adds several important new models and concepts which have been developed in an extremely active research area since the late 1980s. It provides a comprehensive introductory account of event history modeling techniques and their usefulness for causal analysis in the social sciences. By giving many concrete application examples, it demonstrates that event history models allow a natural time-related representation of causal arguments in empirical studies. In contrast to structural equation analysis, which is based upon the observation of states and on "time-less" models, event history analysis employs the time-path of changes in states and relates changes in (qualitative and metric) causal variables in the past to changes in discrete outcomes in the future. Since effects follow their causes in time, this necessarily implies a temporal interval which may be very short or very long, but can never be zero or infinity. This book demonstrates that event history modeling is a major step forward in causal analysis because it is the most appropriate of all currently available methodologies to uncover such (normally unknown) lags between causes and their effects and reveals the various temporal shapes of the unfolding effect. This is because the transition rate can be used to represent the quantity of the causal effect at any point in time. A particular strength of this book lies in the description of a new approach to interdependent dynamical systems. It is shown that a causal approach to interdependent systems is easily possible with the help of the transition rate concept, and that the systems view is not a substitute for a proper causal approach in the social sciences. This book also proposes that the social sciences should give up their traditional deterministic approach in empirical analyses in favor of a probabilistic one. It is argued that randomness should not only be seen as a technical term (arising because of limited empirical observation), but must be understood as a theoretical category; it is the propensity of social agents to change their behavior in the future under certain conditions that have taken place in the past and present. This means that the aim of statistical (and substantive) models must be to capture common elements in the behavior of people, or patterns of action that recur in many cases. In event history models, the causal effect to be explained is therefore the probability of a time-related change. Finally, the book is critical with regard to the widely applied models with unobserved heterogeneity since there is, in general, no way to make reliable assumptions about what has not been observed. Thus, in using such models, most empirical researchers try to draw sharp conclusions, even when these can only be generated by imposing much stronger assumptions than can be plausibly defended. This book introduces the reader to the computer program TDA (Transition Data Analysis). Designed by Götz Rohwer, TDA estimates the kinds of models most frequently used with longitudinal data, in particular, event history data. The guiding principle in constructing TDA was the desire to make a broad range of event history analysis techniques as simple and convenient to apply as possible. TDA is now widely used in many research and university centers which analyze longitudinal data in Europe and the USA. It can be run on DOS-based personal computers and UNIX workstations. Included with this book is a disk with an executable version of the TDA program package for DOS-based machines, a file with the data used in the examples throughout the book, and a series of files containing the TDA set-ups for the examples. Thus, the reader is offered the unique opportunity to easily run and modify all the application examples on the computer. The authors have emphasized the strengths and weaknesses of event history modeling techniques in each example. In particular, they have complemented each practical application with a short exposition of the underlying statistical concepts. The examples start with an introduction to the background for the specific model. Then there is a demonstration of how to organize the input data and use the commands to control the TDA operation. Finally, a substantive interpretation of the obtained results is given.

Techniques of Event History Modeling: New Approaches to Casual Analysis

Including new developments and publications which have appeared since the publication of the first edition in 1995, this second edition: *gives a comprehensive introductory account of event history modeling techniques and their use in applied research in economics and the social sciences; *demonstrates that event history modeling is a major step forward in causal analysis. To do so the authors show that event history models employ the time-path of changes in states and relate changes in causal variables in the past to changes in discrete outcomes in the future; and *introduces the reader to the computer program Transition Data Analysis (TDA). This software estimates the sort of models most frequently used with longitudinal data, in particular, discrete-time and continuous-time event history data. Techniques of Event History Modeling can serve as a student textbook in the fields of statistics, economics, the social sciences, psychology, and the political sciences. It can also be used as a reference for scientists in all fields of research.

Including new developments and publications which have appeared since the publication of the first edition in 1995, this second edition: *gives a comprehensive introductory account of event history modeling techniques and their use in applied research in economics and the social sciences; *demonstrates that event history modeling is a major step forward in causal analysis. To do so the authors show that event history models employ the time-path of changes in states and relate changes in causal variables in the past to changes in discrete outcomes in the future; and  *introduces the reader to the computer program Transition Data Analysis (TDA). This software estimates the sort of models most frequently used with longitudinal data, in particular, discrete-time and continuous-time event history data.  Techniques of Event History Modeling can serve as a student textbook in the fields of statistics, economics, the social sciences, psychology, and the political sciences. It can also be used as a reference for scientists in all fields of research.

Event History Analysis With Stata

Event History Analysis With Stata provides an introduction to event history modeling techniques using Stata (version 9), a widely used statistical program that provides tools for data analysis. The book emphasizes the usefulness of event history models for causal analysis in the social sciences and the application of continuous-time models. The authors illustrate the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data, to data organization, to applications using the software, to the interpretation of results. The book also demonstrates, through example, how to implement hypotheses tests and how to choose the right model. The strengths and limitations of various techniques are emphasized in each example, along with an introduction to the model, details on how to input data, and the related Stata commands. Each application is accompanied by a brief explanation of the underlying statistical concept. Readers are offered the unique opportunity to easily run and modify all of the book’s application examples on a computer, by visiting the author’s Web site at http://www.uni-bamberg.de/sowi/soziologie-i/eha/. Examples include survival rates of patients in medical studies; unemployment periods in economic studies; and the time it takes a criminal to break the law after his release in a criminological study. This new book supplements Event History Analysis, by Blossfeld et al, and Techniques of Event History Modeling, by Blossfeld and Rohwer, extending on their coverage of practical applications and statistical theory. Intended for researchers in a variety of fields such as statistics, economics, psychology, sociology, and political science, Event History Analysis With Stata also serves as a text, in combination with the authors’ other two books, for courses on event history analysis.

Business & Money

Rohwer, Götz

Education & Reference

See the best price to sell, buy, or rent books by Blossfeld, Hans-Peter. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Blossfeld, Hans-Peter

See the best price to sell, buy, or rent books by Blossfeld, Hans-Peter. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Rational Choice Theory And Largescale Data Analysis

The New Role Of Women: Family Formation In Modern Societies

Rational Choice Theory And Largescale Data Analysis

Event History Analysis: Statistical theory and Application in the Social Sciences

Techniques of Event History Modeling: New Approaches To Causal Analysis

Techniques of Event History Modeling: New Approaches To Causal Analysis

Techniques of Event History Modeling: New Approaches to Casual Analysis

Techniques of Event History Modeling: New Approaches to Casual Analysis

Event History Analysis With Stata

Event History Analysis With Stata