Causal inference in longitudinal studies refers to the process of determining whether a specific cause leads to a particular effect by analyzing data collected over an extended period. This approach helps researchers observe changes and patterns over time, allowing them to draw conclusions about the relationships between variables, especially in the context of social inequality. By tracking the same subjects at multiple points in time, it becomes easier to identify potential causal links rather than just correlations.
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