Abstract

The traditional approach to research in Psychology has been to use cross-sectional designs. While temporal methods are not new, they are relatively under-used; however, researchers have been developing methods to analyse temporal dynamics [1 - 3]. Mapping changes in behaviour over time facilitates understanding of causal effects and predicting of future outcomes. To date, there are several main approaches to analysing the influence of variables over time in dynamic systems: Survival Analysis [4 - 5]; Behaviour Sequence Analysis [3], T-Pattern Analysis [6 - 7]; and temporal Social Network Analysis [8 - 9]. All of these methods have proven hugely beneficial in mapping the effects of multiple antecedent factors leading toward different outcomes. The aim of the current presentation is to offer a novel method of temporal measurement, Indicator Waves, which allow multiple simultaneous and sequential events to be analysed across varying time-spans. Indicator waves provide easy-to-read statistical wave diagrams, which are interpretable by a wide range of non-specialist end-users. The waves provide quick inference about which risk factors, behaviours, or events (termed ‘Indicators’) are prevalent across different points in time. The plots at each time point provide a profile of the absence or presence of indicators at that time. The method can be applied to both human and non-human samples.