Janet M. Box-Steffensmeier - Böcker

Political methodology has changed dramatically in the past thirty years. Not only have new methods and techniques been developed, but the Political Methodology Society and the Qualitative Methods Section of the American Political Science Association have engaged in ongoing research and training programs that have advanced both quantitative and qualitative methodology. The Oxford Handbook of Political Methodology is designed to reflect these developments.It provides comprehensive overviews and critiques of all the key specific methodologies. The volume emphasises three things. Firstly, techniques should be the servants of improved data collection, measurement, conceptualization, and the understanding of meanings and the identification of causal relationship in social science research. Techniques will be described with the aim of showing how they contribute to these tasks, and the emphasis will be upon developing good research designs-not upon simply using sophisticated techniques. Second, there are many different ways that these tasks can be undertaken in the social sciences through description and modeling, case-study and large-n designs, and quantitative and qualitative research.Third, techniques can cut across boundaries and be useful for many different kinds of researchers. The chapter authors ask how their methods can be used by, or at least inform, the work of those outside those areas where they are usually employed. For example, those describing large-n statistical techniques should ask how their methods might at least inform, if not sometimes be adopted by, those doing case studies or interpretive work, and we want those explaining how to do comparative historical work or process tracing to explain how it could inform those doing time-series studies.

Political methodology has changed dramatically over the past thirty years, and many new methods and techniques have been developed. Both the Political Methodology Society and the Qualitative/Multi-Methods Section of the American Political Science Association have engaged in ongoing research and training programs that have advanced quantitative and qualitative methodology. The Oxford Handbook of Political Methodology presents and synthesizes these developments.The Handbook provides comprehensive overviews of diverse methodological approaches, with an emphasis on three major themes. First, specific methodological tools should be at the service of improved conceptualization, comprehension of meaning, measurement, and data collection. They should increase analysts' leverage in reasoning about causal relationships and evaluating them empirically by contributing to powerful research designs. Second, the authors explore the many different ways of addressing these tasks: through case-studies and large-n designs, with both quantitative and qualitative data, and via techniques ranging from statistical modelling to process tracing. Finally, techniques can cut across traditional methodological boundaries and can be useful for many different kinds of researchers. Many of the authors thus explore how their methods can inform, and be used by, scholars engaged in diverse branches of methodology.

The 2012 American elections were highly competitive, with the unusually close partisan balance making the elections an opportunity for each of the two major parties. This book assembles leading political scientists and political journalists to explain the 2012 election results and their implications for America’s future.In addition to assessing election results, the book examines the consequences of the large ambitions of the Obama presidency and the political and policy risks entailed in the pursuit of those ambitions. It also explores Congressional elections and policymaking since 2008, and how they affected election results in 2012. The book promises a more coherent focus than that evident in similar edited works, achieved through a limited number of chapters and clear definition of chapter content.

The 2012 American elections were highly competitive, with the unusually close partisan balance making the elections an opportunity for each of the two major parties. This book assembles leading political scientists and political journalists to explain the 2012 election results and their implications for America’s future.In addition to assessing election results, the book examines the consequences of the large ambitions of the Obama presidency and the political and policy risks entailed in the pursuit of those ambitions. It also explores Congressional elections and policymaking since 2008, and how they affected election results in 2012. The book promises a more coherent focus than that evident in similar edited works, achieved through a limited number of chapters and clear definition of chapter content.

Event History Modeling, first published in 2004, provides an accessible guide to event history analysis for researchers and advanced students in the social sciences. The substantive focus of many social science research problems leads directly to the consideration of duration models, and many problems would be better analyzed by using these longitudinal methods to take into account not only whether the event happened, but when. The foundational principles of event history analysis are discussed and ample examples are estimated and interpreted using standard statistical packages, such as STATA and S-Plus. Critical innovations in diagnostics are discussed, including testing the proportional hazards assumption, identifying outliers, and assessing model fit. The treatment of complicated events includes coverage of unobserved heterogeneity, repeated events, and competing risks models. The authors point out common problems in the analysis of time-to-event data in the social sciences and make recommendations regarding the implementation of duration modeling methods.

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.

Event History Modeling, first published in 2004, provides an accessible guide to event history analysis for researchers and advanced students in the social sciences. The substantive focus of many social science research problems leads directly to the consideration of duration models, and many problems would be better analyzed by using these longitudinal methods to take into account not only whether the event happened, but when. The foundational principles of event history analysis are discussed and ample examples are estimated and interpreted using standard statistical packages, such as STATA and S-Plus. Critical innovations in diagnostics are discussed, including testing the proportional hazards assumption, identifying outliers, and assessing model fit. The treatment of complicated events includes coverage of unobserved heterogeneity, repeated events, and competing risks models. The authors point out common problems in the analysis of time-to-event data in the social sciences and make recommendations regarding the implementation of duration modeling methods.

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.