Intensive Longitudinal Models

Abstract

Intensive longitudinal models (ILMs) allow researchers to analyze nested data collected through frequent measurements—typically 20 or more repeated occasions—over densely spaced durations. Rather than being a single statistical approach, ILMs encompass various models unified by their capability to handle densely collected longitudinal data. We briefly summarize the nature of intensive longitudinal designs and why such designs require the use of ILMs. We then provide a classification typology to help readers understand the features of an ILM they should adopt. This classification typology provides the structure for a narrative review of existing ILM research. We conclude with specific recommendations for using ILMs to enhance theory, design, and analysis. Altogether, ILMs are a fairly straightforward extension of longitudinal models many researchers already use, and so we encourage their application to a broader range of theories and topics.