Longitudinal
In Data Science, longitudinal refers to a type of study or analysis that involves collecting data from the same subjects over a period of time. This type of study is often used to observe changes or trends in the data over time, and can be particularly useful in fields such as healthcare, psychology, and social sciences. Longitudinal studies can be either prospective, where data is collected in the future, or retrospective, where data is collected from the past. The data collected in longitudinal studies can be analyzed using various statistical methods, such as linear mixed models, growth curve models, and survival analysis. Longitudinal data can also be used to develop predictive models, such as time series forecasting models, that can be used to forecast future trends or outcomes based on past data.
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