ABSTRACT
Rogosa's 1988 chapter “Myths about longitudinal research” challenged many classic assumptions about the analysis of change. Unfortunately, Rogosa's work is not widely enough followed even today. Many scientists and reviewers just assume that change scores are unreliable, that the analysis of covariance with time-1 scores as the covariate is an appropriate way for studying change, that regression toward the mean is almost a law of nature, and so on. Rogosa's work shows that many of these assumptions are wrong. He also offers a viable alternative. In this chapter, the original “Myths about longitudinal research” chapter is reprinted, augmented by new material on data analysis and the measurement of change in the form of supplemental questions and answers.
