We are living through a period of dramatic political change – Brexit, the election of Trump, the rise of extreme right movements in Europe and elsewhere, the resurgence of nationalism and xenophobia and a concerted assault on the liberal values and ideals associated with cosmopolitanism and globalization. Suddenly we find ourselves in a world that few would have imagined possible just a few years ago, a world that seems to many to be a move backwards. How can we make sense of these dramatic developments and how should we respond to them? Are we witnessing a worldwide rejection of liberal democracy and its replacement by some kind of populist authoritarianism? This timely volume brings together some of the world's greatest minds to analyse and seek to understand the forces behind this 'great regression'. Writers from across disciplines and countries, including Paul Mason, Pankaj Mishra, Slavoj Zizek, Zygmunt Bauman, Arjun Appadurai, Wolfgang Streeck and Eva Illouz, grapple with our current predicament, framing it in a broader historical context, discussing possible future trajectories and considering ways that we might combat this reactionary turn. The Great Regression is a key intervention that will be of great value to all those concerned about recent developments and wondering how best to respond to this unprecedented challenge to the very core of liberal democracy and internationalism across the world today. For more information, see: www.thegreatregression.eu

Providing beginners with a background to the frequently-used technique of linear regression, this text provides a heuristic explanation of the procedures and terms used in regression analysis and has been written at the most elementary level.

′The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.′ - John Fox, Professor, Department of Sociology, McMaster University ′The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.′ - Ben Jann, Executive Director, Institute of Sociology, University of Bern ′Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for both cross-sectional and panel data analysis.′ -Tom Smith, Senior Fellow, NORC, University of Chicago Edited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities. Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method’s logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method’s application, making this an ideal text for PhD students and researchers embarking on their own data analysis.

Does the stability of personality vary by gender or ethnicity? Does a particular therapy work better to treat clients with one type of personality disorder than those with another? Providing a solution to thorny problems such as these, Aguinis shows readers how to better assess whether the relationship between two variables is moderated by group membership through the use of a statistical technique, moderated multiple regression (MMR). Clearly written, the book requires only basic knowledge of inferential statistics. It helps students, researchers, and practitioners determine whether a particular intervention is likely to yield dissimilar outcomes for members of various groups. Associated computer programs and data sets are available at the author's website (http: //mypage.iu.edu/ haguinis/mmr).

This book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models. Plots are shown to be an important tool for both building regression models and assessing their validity. We shall see that deciding what to plot and how each plot should be interpreted will be a major challenge. In order to overcome this challenge we shall need to understand the mathematical properties of the fitted regression models and associated diagnostic procedures. As such this will be an area of focus throughout the book. In particular, we shall carefully study the properties of resi- als in order to understand when patterns in residual plots provide direct information about model misspecification and when they do not. The regression output and plots that appear throughout the book have been gen- ated using R. The output from R that appears in this book has been edited in minor ways. On the book web site you will find the R code used in each example in the text.

Officially over in 2009, the Great Recession is now generally acknowledged to be the most devastating global economic crisis since the Great Depression. As a result of the crisis, the United States lost more than 7.5 million jobs, and the unemployment rate doubled—peaking at more than 10 percent. The collapse of the housing market and subsequent equity market fluctuations delivered a one-two punch that destroyed trillions of dollars in personal wealth and made many Americans far less financially secure. Still reeling from these early shocks, the U.S. economy will undoubtedly take years to recover. Less clear, however, are the social effects of such economic hardship on a U.S. population accustomed to long periods of prosperity. How are Americans responding to these hard times? The Great Recession is the first authoritative assessment of how the aftershocks of the recession are affecting individuals and families, jobs, earnings and poverty, political and social attitudes, lifestyle and consumption practices, and charitable giving. Focused on individual-level effects rather than institutional causes, The Great Recession turns to leading experts to examine whether the economic aftermath caused by the recession is transforming how Americans live their lives, what they believe in, and the institutions they rely on. Contributors Michael Hout, Asaf Levanon, and Erin Cumberworth show how job loss during the recession—the worst since the 1980s—hit less-educated workers, men, immigrants, and factory and construction workers the hardest. Millions of lost industrial jobs are likely never to be recovered and where new jobs are appearing, they tend to be either high-skill positions or low-wage employment—offering few opportunities for the middle-class. Edward Wolff, Lindsay Owens, and Esra Burak examine the effects of the recession on housing and wealth for the very poor and the very rich. They find that while the richest Americans experienced the greatest absolute wealth loss, their resources enabled them to weather the crisis better than the young families, African Americans, and the middle class, who experienced the most disproportionate loss—including mortgage delinquencies, home foreclosures, and personal bankruptcies. Lane Kenworthy and Lindsay Owens ask whether this recession is producing enduring shifts in public opinion akin to those that followed the Great Depression. Surprisingly, they find no evidence of recession-induced attitude changes toward corporations, the government, perceptions of social justice, or policies aimed at aiding the poor. Similarly, Philip Morgan, Erin Cumberworth, and Christopher Wimer find no major recession effects on marriage, divorce, or cohabitation rates. They do find a decline in fertility rates, as well as increasing numbers of adult children returning home to the family nest—evidence that suggests deep pessimism about recovery. This protracted slump—marked by steep unemployment, profound destruction of wealth, and sluggish consumer activity—will likely continue for years to come, and more pronounced effects may surface down the road. The contributors note that, to date, this crisis has not yet generated broad shifts in lifestyle and attitudes. But by clarifying how the recession’s early impacts have—and have not—influenced our current economic and social landscape, The Great Recession establishes an important benchmark against which to measure future change.

Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software. The 2003 book is suitable as a textbook for students with little background in regression as well as a reference book for statistically oriented scientists such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models. Even experts on semiparametric regression should find something new here.