• Longitudinal;
  • Dynamic systems;
  • Development;
  • Person-oriented;
  • Cluster analysis;
  • Grades


An approach is presented for studying individual pattern development in person-oriented terms focusing on the concept of i-state, i.e. an individual's configuration of information at a specific point in time. The procedure is called I-States as Objects Analysis (ISOA). First common i-states (typical states) are identified using cluster analysis of subindividuals and then this information is used for describing typical developmental patterns. Both a general procedure and a specific procedure used on a demonstration data set were developed. Using ISOA, change and stability can be studied both with regard to structure and with regard to individual variation. An empirical example was given which concerned longitudinal data about school grades at four different ages for 333 boys and girls. The data were split into a test sample and a replication sample of equal sizes. It was contended from the empirical study that ISOA functioned reasonably well on the sample studied. In the discussion, it was pointed out that ISOA can be a powerful method to use for small samples with many measurement occasions and that the method is optimal for studying short-term change.