A longitudinal study is a quasi-experimental research design that involves repeated observations of the same variables (e.g., people) over long periods of time, often many decades (i.e., uses longitudinal data). It is often a type of observational study, although they can also be structured as longitudinal randomized experiments.
Longitudinal studies are often used in psychology, to study developmental trends across the life span, and in sociology, to study life events throughout lifetimes or generations. The reason for this is that unlike cross-sectional studies, in which different individuals with the same characteristics are compared, longitudinal studies track the same people and so the differences observed in those people are less likely to be the result of cultural differences across generations. Longitudinal studies thus make observing changes more accurate and are applied in various other fields.
In medicine, the design is used to uncover predictors of certain diseases. In advertising, the design is used to identify the changes that advertising has produced in the attitudes and behaviors of those within the target audience who have seen the advertising campaign. Longitudinal studies allow social scientists to distinguish short from long-term phenomena, such as poverty.
If the poverty rate is 10% at a point in time, this may mean that 10% of the population are always poor or that the whole population experiences poverty for 10% of the time. It is impossible to conclude which of these possibilities is the case by using one-off cross-sectional studies.
Longitudinal Study Pros And Cons
When longitudinal studies are observational, in the sense that they observe the state of the world without manipulating it, it has been argued that they may have less power to detect causal relationships than experiments.
However, because of the repeated observation at the individual level, they have more power than cross-sectional observational studies, by virtue of being able to exclude time-invariant unobserved individual differences and also of observing the temporal order of events.
Some of the disadvantages of longitudinal study are that they take a lot of time and are very expensive. Therefore, they are not very convenient.
Longitudinal studies can be retrospective (looking back in time, thus using existing data such as medical records or claims database) or prospective (requiring the collection of new data).
Types of longitudinal studies include cohort studies, which sample a cohort (a group of people who share a defining characteristic, typically who experienced a common event in a selected period, such as birth or graduation) and perform cross-section observations at intervals through time (not all longitudinal studies are cohort studies, as it can be a group of people who do not share a common event).
Some examples of longitudinal studies include the Alzheimer’s Disease Neuroimaging Initiative, an international panel study from 2004 www.adni-info, the Children of Immigrants Longitudinal Study (CILS), a U.S. cohort study from 1992 involving 5,262 participants, and the Scottish Longitudinal Study, which comprises 5.3% sample of the Scottish population, and holds records on approximately 274,000 individuals using 20 random birthdates from 1991 onwards.
Shadish, William R.; Cook, Thomas D.; Campbell, Donald T. (2002)
Experimental and Quasi-Experimental Designs for Generalized Causal Inference (2nd ed.)
Boston: Houghton Mifflin Company. ISBN 0-395-61556-9.