I-states-as-objects-analysis (ISOA): Extensions of an approach to studying short-term developmental processes by analyzing typical patterns

Abstract

I-states-as-objects-analysis (ISOA) is a person-oriented methodology for studying short-term developmental stability and change in patterns of variable values. ISOA is based on longitudinal data with the same set of variables measured at all measurement occasions. A key concept is the i-state, defined as a person’s pattern of variable values at a specific time point. All i-states are first subjected to a classification analysis that results in a time-invariant classification characterized by a number of typical i-states. Each person is then characterized at each time point by the typical i-state he/she belongs to. Then the person’s sequences of typical i-states are analyzed with regard to structural and individual stability and change. Extensions of ISOA are presented where: (1) some methods for checking the assumption of a time-invariant classification are indicated; (2) information about the degree of dissimilarity between typical i-states is used as an aid in interpreting the findings; and (3) attention is given to closed paths—that is, typical i-state sequences that do not occur at all. To demonstrate the methods, an empirical example is given that concerns the development of children’s achievement-intelligence patterns between ages 10 and 13.

Forms of friendship: A person-centered assessment of the quality, stability, and outcomes of different types of adolescent friends

“…To test the assumption of over-time structural invariance, we compared the squared Euclidian distance of the centroids from the ISOA solution to the time 1 centroids from the Ward’s clustering procedure. Distances less than 0.25 are considered acceptable (Bergman, Nurmi, von Eye & 2012). The mean distance between the solutions was 0.06, confirming the assumption of over-time structural invariance and indicating the appropriate use of ISOA.…”

“…The squared Euclidian distance of the centroids obtained from the Study 1 cluster solution were compared to those from the Study 2 cluster solution to quantify the similarity of the friendship clusters. Distances should be less than 2 to be considered comparable (Bergman, Nurmi, & von Eye, 2012). …”

“…Two types of I-States as Objects Analyses (ISOA; Bergman, Nurmi & von Eye, 2012) were designed for this purpose. Structural stability analyses determine whether the same proportion of dyads fall into same cluster group at each time point, comparing cell types (populated at greater than chance levels) and antitypes (populated at less than chance levels) in the 6 th grade and in the 7 th grade.…”

Nurses' beliefs about nursing diagnosis: A study with cluster analysis

“…According to a systematic review the TPB has helped the health sciences to explain and predict several healthcare provider behaviours (Godin, Belanger‐Gravel, Eccles, & Grimshaw, ) and clearly offers the investigators a theoretically sound framework for these purposes. Regarding the nursing profession, the TPB gives a good explanation of some nurses' behaviours, such as the correct measurement of blood pressure (Nelson, Cook, & Ingram, ), the reporting of suspected child abuse (Bergman, Nurmi, & Alexander, ) and the reporting of adverse drug reactions (Angelis et al., ). Prior studies have already found that attitudes towards the use of ND influences ND use in clinical practice (D'Agostino et al., ; de Souza Guedes et al., ; Romero‐Sanchez et al., ), however, it is noted that none of these studies considered behavioural, normative and control beliefs about ND use.…”

The person-oriented approach: A short theoretical and practical guide

“…In this way, structural and individual stability and change can be studied at the pattern level. Another method is I-States as Objects Analysis -ISOA (Bergman, Nurmi, & von Eye, 2012). In ISOA, shortterm development in a set of variables is studied by first finding a timeinvariant classification system, usually by employing cluster analysis.…”