This book of worked-out examples not only accompanies Timothy M Hagle's earlier book Basic Math for Social Scientists: Concepts but also provides an informal refresher course in algebra sets, limits and continuity, differential calculus, multivariate functions, partial derivatives, integral calculus and matrix algebra. Problem sets are also provided so that readers can practice their grasp of standard mathematical procedures.
This book provides an introduction to the re gression models needed, where an outcome variable for a samp le is not representative of the population from which a gene ralized result is sought. '
What is chaos? How can it be measured? How are the models estimated? What is catastrophe? How is it modelled? How are the models estimated? These questions are the focus of this volume. Beginning with an explanation of the differences between deterministic and probabilistic models, Brown then introduces the reader to chaotic dynamics. Other topics covered are finding settings in which chaos can be measured, estimating chaos using nonlinear least squares and specifying catastrophe models. Finally a nonlinear system of equations that models catastrophe using real survey data is estimated.
Which time series test should researchers choose to best describe the interactions among a set of time series variables? Providing guidelines for identifying the appropriate multivariate time series model to use, this book explores the nature and application of these increasingly complex tests. In addition, it covers such topics as: joint stationarity; testing for cointegration; testing for causality; and model order and forecast accuracy. Related models explained include transfer function, vector autoregression and error correction models.
Logit, Probit, and Other Generalized Linear Models
What is the probability that something will occur, and how is that probability altered by a change in an independent variable? To answer these questions, Tim Futing Liao introduces a systematic way of interpreting commonly used probability models. Since much of what social scientists study is measured in noncontinuous ways and, therefore, cannot be analyzed using a classical regression model, it becomes necessary to model the likelihood that an event will occur. This book explores these models first by reviewing each probability model and then by presenting a systematic way for interpreting the results from each.
Blending the tenets of Marxist theory with many of the more traditional methods of social science, this accessible book is a brief introduction to the major ideas and scholars in the Analytical Marxist school. The author assesses the achievements, strengths and criticisms of the work of Elster, Roemer, Wright and others, examining their writings on class, the state, exploitation and revolution. The book explores the challenge to Marxist thought brought about by contemporary developments in Eastern Europe and suggests how the future of Marxism is shaped by these events.
What is the role of fit measures when respecifying a model? Should the means of the sampling distributions of a fit index be unrelated to the size of the sample? Is it better to estimate the statistical power of the chi-square test than to turn to fit indices? Exploring these and related questions, well-known scholars examine the methods of testing structural equation models (SEMS) with and without measurement error, as estimated by such programs as EQS, LISREL and CALIS.
When using the analysis of variance (ANOVA) in an experimental design, how can the researcher determine whether to treat a factor as fixed or random? This book provides the reader with the criteria to make the distinction between fixed and random levels among factors, an important decision that directly reflects the purpose of the research. In addition to exploring the varied roles random factors can play in social research, the authors provide a discussion of the statistical analyses required with random factors and give an overview of computer-assisted analysis of random factor designs using SAS and SPSSX.
This volume offers a reappraisal of sociologist Talcott Parsons' work by social theorists who place his writing at the centre of current controversies over modernity, postmodernity and globalization. The contributors examine the problems in the interpretation of Parsons' work. The discussion encompasses his place in American social theory, his conception of world history and the contemporary neo-functionalist movement.
