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Longitudinal data is the result of a type of long-term observation called a longitudinal study. These studies focus on a select group of people or processes and observe how various factors change for them over time. These studies are multi-dimensional, which means they look at many different aspects of the studied subject rather than focus on one particular area. Longitudinal data is used to find long-term trends in a person’s life or in an ongoing process that would be impossible to see in a one-time study.
The defining factors for longitudinal data are time and complexity. In order for the study to actually be longitudinal, it must examine a factor repeatedly over a period long enough to see progression in that factor. During that time, the subject repeatedly answers questions with statistical data and anecdotal information.
This time frame varies based on the type of study being conducted. If the study is on the effects of the second year of college on women from the US state Ohio, then that particular group needs to routinely supply data for one year. Should the study relate to the effects poverty has on children’s work habits, then the kids need to supply data from when they are very young until they are old enough to have established professions. This study would likely go on from about age 5 to around 30 and possibly even longer.
The other factor, complexity, is what allows people studying the longitudinal data to pick out trends. The information supplied by the test subjects covers aspects that don’t seem to have any impact on the areas being tested. This allows researchers to find environmental and social trends that influence seemingly unrelated behaviors. It also allows them to find something called a spurious connection. These are points that seem related, but closer examination reveals they are simply two factors influenced by a third.
These studies are used in many areas of anthropology and sociology, but other fields use them as well. Economics uses longitudinal data to find trends in markets. These trends have a tendency to repeat if given enough time. With enough information, an investor can spot trends happening currently that mimic complex trends that happened in the past, giving him a better understanding of how to invest.
Manufacturing companies use longitudinal data to find ways to improve their products and increase the lifespans of equipment. By picking out trends, they are able to separate one-off problems and circumstances from repeating incidents. This lets them focus their energy, and money, more efficiently.
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