Longitudinal data analysis has received widespread interest throughout educational, behavioral, and social science research, with latent growth curve modeling currently being one of the most popular methods of analysis. Despite the popularity of latent growth curve modeling, limited attention has been directed toward understanding the issues of reliability of measurement change in the context of this method. The purpose of this article is to outline the common difficulties that arise when estimating reliability within the context of growth models and extend the notion of reliability to a more general modeling framework that takes into account the specifics of longitudinal data. To highlight the importance of focusing on reliability of measurement change in the context of latent growth curve modeling, empirical data are examined.