A dynamic factor model for the analysis of multivariate time series

As a method to ascertain the structure of intra-individual variation,P-technique has met difficulties in the handling of a lagged covariance structure. A new statistical technique, coined dynamic factor analysis, is proposed, which accounts for the entire lagged covariance function of an arbitrary second order stationary time series. Moreover, dynamic factor analysis is shown to be applicable to a relatively short stretch of observations and therefore is considered worthwhile for psychological research. At several places the argumentation is clarified through the use of examples.I would like to thank WM. van der Molen, G. J. Mellenbergh and L. H. M. Oppenheimer, who provided valuable ideas that led to this formulation.     

A time series analysis of the relation between motor skill acquisition and sleep in infancy

To systematically examine the relation between motor milestone onset and disruption of night sleep in infancy, three families kept microgenetic, prospective, daily checklist diaries of their infants’ motor behavior and sleep (197-313 observation days; 19,000 diary entries). Process control and interrupted time series analyses examined whether deviations from the moving average for night wakings and evening sleep duration were temporally linked to motor skill onset and tested for meaningful differences in individual sleep patterns before and after skill onset. Model assumptions defined skill onset as first day of occurrence or as mastery and moving average windows as 3, 7, or 14 days. Changes in infants’ sleep patterns were associated with changing expertise for motor milestones. The temporal relation varied depending on infant and sleep parameter. Intensive longitudinal data collection may increase our understanding of micro-events in infant development.     

A cognitive multivariate time series and its analysis

The method of analyzing a multivariate time series, by factoring a matrix polynomial of linear transfer function coefficients, is briefly outlined and shown to be potentially applicable to cognitive experiments where the inputs are numerically predictable and the outputs suitably quantified. An experiment on sequences of 90 figures, judged in terms of similarity and of the probability of exceeding or not exceeding some size, was analyzed individually for 12 subjects and their dynamic characteristics expressed in pole zero diagrams. Some dynamic components neglected by classical time-independent psychological methods are identified.     

Windowed cross-correlation and peak picking for the analysis of variability in the association between behavioral time series

Cross-correlation and most other longitudinal analyses assume that the association between 2 variables is stationary. Thus, a sample of occasions of measurement is expected to be representative of the association between variables regardless of the time of onset or number of occasions in the sample. The authors propose a method to analyze the association between 2 variables when the assumption of stationarity may not be warranted. The method results in estimates of both the strength of peak association and the time lag when the peak association occurred for a range of starting values of elapsed time from the beginning of an experiment.     

Investigating the relationship between employability and self-efficacy: A cross-lagged analysis

The construct of employability has been conceptually related to self-efficacy in different ways. Employability has sometimes been regarded as an equivalent to self-efficacy, or as a distinct but related phenomenon. Since the relationship between the two phenomena has not been subjected to empirical scrutiny, the aim of the present study is to analyze whether self-efficacy and employability are two distinct but related constructs, and if they are, to investigate the direction of their relationship. The data (N = 1730) were collected through a two-wave longitudinal survey with one year between each data collection (2005 and 2006). The results of confirmatory factor analysis showed that the measures of employability and self-efficacy were distinct from one another, within and over measurement points, indicating that these are related but separate constructs. The results of latent variable cross-lagged analysis showed that employability predicted subsequent self-efficacy, even after controlling for age, gender, educational level, and regional differences. Thus, employability is not an expression of efficacy beliefs, but rather, the strengthening of employability perceptions may have beneficial effects on more general efficacy beliefs.     

The relationship between leisure time and driving style in two groups of male drivers

Despite overall improvements in traffic safety levels, young male drivers continue to be over represented in accidents. In this study the association between driving style and leisure time was examined in two groups of drivers. The sample consisted of 4000 male drivers of which 2000 were 18 years old and 2000 were 28 years old. A posted questionnaire was used. The overall response rate was 51% (N = 2018). A similar factor structure of three factors with regard to driving style was identified in both groups of drivers. The factors were named Thrill, Anxiety and Anger. Despite significant differences regarding specific leisure time activities, a similar relationship between leisure time and driving style was found in the two groups of drivers particularly in relation to problem behaviours. In both groups driving related interaction with friends as well as a high paced leisure time was found to be related to a high score on the factors Thrill and Anger. In the older group of drivers cruising with friends was associated with problem behaviours such as smoking pot and doing drugs. Results indicate a need for early intervention enhancing safe behavioural choices thereby preventing unsafe behaviours to become permanent behavioural strategies in life.