Longitudinal Data Analysis

Differences Between Longitudinal Studies and Cross-Sectional Studies

Longitudinal designs focus on tracking change in behavior seen by observing subjects over a period of time. Providing observations on the subject beyond one point in time, this design allows researchers to track the variations or development of characteristics of a target population in both individual and group levels. A significant advantage of longitudinal data collection is that it is able to distinguish a time-varying effect (i.e., variability of particular characteristics occurred within an individual) from a cohort effect (i.e., difference between individuals in different age-groups).

Unlike longitudinal design, cross-sectional design does not provide repeated measurements on the data over time. It aims to describe the particular characteristics of the subjects at a single point in time. Cross-sectional studies are sometimes carried out to examine the links between different predictors and the outcome of interests.

Cross-sectional design is less effective in explaining cause-and-effect relationships than longitudinal designs because it is unable to show any indication of the order of the measured events. It also fails to provide definite information for distinguishing between cohort and time-varying effects. For instance, when investigating the age effect on social competence among adolescents, the finding of a cross-sectional design might indicate that older adolescents tend to have a higher level of social competence. In contrast, longitudinal research design can distinguish the effect that is due to increased age from the effect that is caused by individual differences. It also generates a trajectory of social competence to show the pattern of change.

Forms and Characteristics of Longitudinal Study Designs and Analysis

Longitudinal designs and data analysis has undergone a period of rapid development over the [Page 1000]past 2 decades. There are four common forms of longitudinal design, namely, repeated cross-sectional study, panel design, event-oriented design (event history data), and qualitative longitudinal studies.