Why Aren't You Writing?: Research, Real Talk, Strategies, & Shenanigans describes research on how bright and otherwise fairly normal people lose their minds when it comes to writing, and then shows the reader how to stop being one of those people. Author Sharon Zumbrunn designed this brief text for new academics and graduate students so they can understand the psychological hang-ups that can get in the way of writing productivity.
A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression.
Techniques for Longitudinal and Contextual Analysis
This comprehensive text introduces regression, the general linear model, structural equation modeling, the hierarchical linear model, growth curve models, panel data, and event history models, and includes discussion of published implementations of each technique showing how it was used to address substantive and interesting research questions. It takes a step-by-step approach in the presentation of each topic, using mathematical derivations where necessary, but primarily emphasizing how the methods involved can be implemented, are used in addressing representative substantive problems than span a number of disciplines, and can be interpreted in words. The book demonstrates the analyses in STATA and SAS.
Including many interesting example analyses and interpretations, along with exercises, this text offers a practical introduction to multiple regression. Each dataset used for the examples and exercises is small enough for readers to easily grasp the entire dataset and its analysis with respect to the specific statistical techniques covered. SPSS, Stata, SAS, and R code and commands for each type of analysis or recoding of variables in the book are available on an accompanying website, along with solutions to the exercises (on the instructor site).
Engaging and thoroughly updated, this text provides a global perspective on the use and regulation of legal and illegal drugs. It examines drug policies in terms of their scope, goals, and effectiveness, as well as the effects of drugs, the patterns and correlates of use, and theories of the causes of drug use.
This book introduces current perspectives on Rasch measurement theory with an emphasis on developing Rasch-based scales. Rasch measurement theory represents a paradigm shift in measurement theory away from classical test theory and creates a framework for scaling that can yield invariant measurement. Rasch Models for Solving Measurement Problems: Invariant Measurement in the Social Sciences is a broadly accessible text. Authors George Engelhard Jr and Jue Wang introduce Rasch measurement theory step by step, with chapters on scale construction, evaluation, maintenance, and use. Points are illustrated and techniques are demonstrated through an extended example: The Food Insecurity Experience (FIE) Scale. The Rasch analyses in the book are run using the Facets computer program. Facets syntax, and R code for the ERMA program created by the authors to obtain parameter estimates and to examine model-data fit, together with sample data sets are all available on a website for the book.
Correlation matrices (along with their unstandardized counterparts, covariance matrices) underlie the majority the statistical methods that researchers use today. A correlation matrix is more than a matrix filled with correlation coefficients. The value of one correlation in the matrix puts constraints on the values of the others, and the multivariate implications of this statement is a major theme of the volume. Alexandria Hadd and Joseph Lee Rodgers cover many features of correlations matrices including statistical hypothesis tests, their role in factor analysis and structural equation modeling, and graphical approaches. They illustrate the discussion with a wide range of lively examples including correlations between intelligence measured at different ages through adolescence; correlations between country characteristics such as public health expenditures, health life expectancy, and adult mortality; correlations between well-being and state-level vital statistics; correlations between the racial composition of cities and professional sports teams; and correlations between childbearing intentions and childbearing outcomes over the reproductive life course. This volume may be used effectively across a number of disciplines in both undergraduate and graduate statistics classrooms, and also in the research laboratory.
Families & Change: Coping With Stressful Events and Transitions presents current literature detailing families' responses to varied transitions and stressful life events over the life span.
How can an undergraduate college education prepare learners to cope with the current COVID-19 pandemic? This collection of short essays, written by experts in 25 academic fields of study, addresses this very question. Each chapter brings perspective and insight from that discipline, presenting one useful idea and a recommended course of action. This one-of-a-kind resource is ideal for students, instructors, and administrators, particularly during the 2020-2021-academic year when institutions are challenged to continue their educational missions in the midst of a public health crisis that affects every aspect of college life.
