Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. In addition to these natural changes, targeted interventions may cause change: cholesterol levels may decline as a result of a new medication, exam grades may rise following completion of a coaching class. By measuring and charting changes like these - both naturalistic and experimentally induced - researchers uncover the temporal nature of development. The investigation of change has fascinated empirical researchers for generations, and to do it well, they must have longitudinal data.

Applied Longitudinal Data Analysis is a much-needed professional book that will instruct readers in the many new methodologies now at their disposal to make the best use of longitudinal data, including both individual growth modelling and survival analysis. Throughout the chapters, the authors employ many cases and examples from a variety of disciplines, covering multilevel models, curvilinear and discontinuous change, in addition to discrete-time hazard models, continuous-time event occurrence, and Cox regression models. Applied Longitudinal Data Analysis is a unique contribution to the literature on research methods and will be useful to a wide range of behavioural and social science researchers.

Will America find enough good teachers to staff its public schools? How can we ensure that all our children will be taught by skilled professionals? The policies that determine who teaches today are a confusing and often conflicting array that includes tougher licensing requirements, higher salaries, mandatory master's degrees, merit pay, and alternative routes to certification. Who Will Teach? examines these policies and separates those that work from those that backfire. The authors present an intriguing portrait of America's teachers and reveal who they are, who they have been, and who they will be. Using innovative statistical methods to track the professional lives of more than 50,000 college graduates, the book describes, in many cases for the first time, just how prospective, current, and former teachers respond to the incentives and disincentives they face. The authors, a group of noted educators, economists, and statisticians, find cause for serious concern. Few academically talented college graduates even try teaching, and many of those who do leave quickly, never to return. Current licensing requirements stifle innovation in training and dissuade many potentially talented teachers at the outset. But Who Will Teach? shows that we can reverse these trends if we get the incentives right. Although better salaries are essential, especially for new teachers, money is not enough. Potential teachers should be offered alternative paths into the classroom. School districts should improve their recruiting strategies. Licensing criteria should assess teaching skills, not just academic achievement and number of courses completed. The authors offer a promising strategy based on high standards and substantial rewards.

Do students who work longer and harder learn more in college? Does joining a fraternity with a more academic flavor enhance a student's academic performance? When are the results from an innovation that is tried on one campus applicable to other campuses? How many students and faculty members must participate in a research project before findings are valid? Do students learn best when they study alone or in small groups?

These are just some more than fifty examples that Richard Light Judith Singer and John Willett explore in "By Design," a lively nontechnical sourcebook for learning about colleges and universities. These authors believe that careful design of research on college effectiveness is the single most important step toward producing useful and valid findings. In that spirit, "By Design" is a pathbreaking textbook of modern research methods that both practitioners and students will find useful.