When Measures Change over Time: A Workable Solution for Analysing Change and Growth across Multiple Waves

In the past 20 years, the analysis of individual change has become a key focus in educational research. There are several parametric analyses that centre upon quantifying change. Some researchers state that such analyses should only occur if the measure itself remains completely unchanged across waves, arguing that it is not possible to link or connect the scores, either methodologically or conceptually, of measures whose content, wording, response categories, or response formats vary across waves. Because it is not always possible or warranted to use the exact same measure over time, however, it is vital to explore more fully the problem of analysing change and growth with measures that vary across waves. To this end, the primary objective of this paper is to expand upon the statistical work of Lloyd and Zumbo (2007) by introducing the non-parametric hierarchical linear model (NPAR-HLM), a workable solution to the problem of analysing change/growth with measures that change over multiple waves. An example of the implementation of the solution is provided, as is a discussion of the solution’s assumptions, strengths, and limitations