Compilation of papers to illustrate the efficiency and accuracy of quantitative research methods and statistical methods applied in experimental social research and economic research - comprises an evaluation of the application of quantitative analysis to studies on public opinion on politics, election behaviour, health hazards, aspects of social psychology, the social implications of economic growth, educational surveys, etc., made in the USA, examines data analysis methodologys and includes literature surveys. References and statistical tables.

Presents a sense of sociological attitude and appreciation of world problems.

*HH06, The Analysis of Social Problems, Linda R. Weber(State University of New York), H4166-8, 300 pp., 6 x 9, 0-205-14166-8, paperbound, 1995, $15.00nk, November*/This book takes an analytical approach to the study of social problems. The author develops a conceptual framework from which to understand social problems, helping students integrate detailed materials found in traditional social problems books. The book provides readers who have no sociological background with an overview background of sociology, its theory and methods.

Uniquely focusing on intersections of social problems, multilevel statistical modeling, and causality; the substantively and methodologically integrated chapters of this book clarify basic strategies for developing and testing multilevel linear models (MLMs), and drawing casual inferences from such models. These models are also referred to as hierarchical linear models (HLMs) or mixed models. The statistical modeling of multilevel data structures enables researchers to combine contextual and longitudinal analyses appropriately. But researchers working on social problems seldom apply these methods, even though the topics they are studying and the empirical data call for their use. By applying multilevel modeling to hierarchical data structures, this book illustrates how the use of these methods can facilitate social problems research and the formulation of social policies. It gives the reader access to working data sets, computer code, and analytic techniques, while at the same time carefully discussing issues of causality in such models. This book innovatively: •Develops procedures for studying social, economic, and human development. • Uses typologies to group (i.e., classify or nest) the level of random macro-level factors. • Estimates models with Poisson, binomial, and Gaussian end points using SAS's generalized linear mixed models (GLIMMIX) procedure. • Selects appropriate covariance structures for generalized linear mixed models. • Applies difference-in-differences study designs in the multilevel modeling of intervention studies. •Calculates propensity scores by applying Firth logistic regression to Goldberger-corrected data. • Uses the Kenward-Rogers correction in mixed models of repeated measures. • Explicates differences between associational and causal analysis of multilevel models. • Consolidates research findings via meta-analysis and methodological critique. •Develops criteria for assessing a study's validity and zone of causality. Because of its social problems focus, clarity of exposition, and use of state-of-the-art procedures; policy researchers, methodologists, and applied statisticians in the social sciences (specifically, sociology, social psychology, political science, education, and public health) will find this book of great interest. It can be used as a primary text in courses on multilevel modeling or as a primer for more advanced texts.

"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--

This book covers a wide range of contemporary methods for researching social problems and connects these approaches to the broader substance and theories of social problems. Expository and discursive in approach, chapters follow a uniform structure, with each offering research examples and a broad description of the related method and its theoretical context, together with a "how-to" guide for applying that method using substantive examples from the field of social problems. For every method explored, there is a research example that fully reviews and illustrates the application of the particular method, before giving a full assessment of the method’s strengths and weaknesses and latest developments. With chapters exploring survey interviews, in-depth interviews, narrative inquiry, institutional ethnography, participatory action research, auto-ethnography, Actor-Network Theory, experimental research, visual research methods, and research ethics, Researching Social Problems will appeal to scholars and students of sociology and politics working in the fields of research methods and social problems.