Final answer:
The difference between cross-sectional and longitudinal studies in the context of older driver fatalities largely lies in the different time frames considered; cross-sectional studies provide a snapshot, while longitudinal studies track changes over time.
Step-by-step explanation:
The question concerns the reasons why cross-sectional and longitudinal studies might give different results when researching older driver fatalities. Cross-sectional studies involve analyzing data from a population at one specific point in time, often comparing different groups (e.g., by age). In contrast, longitudinal studies observe the same subjects repeatedly over time. The reason for different results between these study types is often due to (c) Different time frames considered in the methodology. Longitudinal studies consider how individuals or populations change over time, giving insight into trends and developments, while cross-sectional studies provide a snapshot of data at a single point in time, which might highlight differences between groups but doesn't show how these differences evolve.
For instance, in a longitudinal study looking at older driver fatalities, one could monitor the same group of drivers over a number of years to observe how their fatality rates change as they age. Conversely, a cross-sectional study would look at different age groups at one point in time, which wouldn't account for changes over time and might be influenced by cohort effects. These are the differences that exist between generations not because of their age per se, but because of the distinct social and cultural experiences that make each generation unique.