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Recovering event histories by cubic spline interpolation
Mathematical Population Studies
|January 1, 1989
Summary
Converting time-interval data, like census age at marriage, can cause errors. This study uses cubic spline interpolation to adjust these schedules, resolving discrepancies found in US census data.
Area of Science:
- Demography
- Statistical Methods
- Data Analysis
Background:
- Event data recorded in discrete time intervals can introduce errors when converted to other units (e.g., age, duration).
- Inconsistent age at marriage schedules in US censuses highlight this data conversion problem.
Purpose of the Study:
- To develop a general method for correcting errors in time-interval data conversion.
- To adjust US age at marriage schedules using a novel interpolation technique.
Main Methods:
- Utilizing cubic spline interpolation as a general method for data adjustment.
- Applying the method to US age at marriage data from 1960 and 1970 censuses.
Main Results:
- The cubic spline interpolation method effectively adjusts age at marriage schedules.
- The adjusted schedules explain a significant portion of the discrepancies between the 1960 and 1970 US censuses.
Conclusions:
- Cubic spline interpolation provides a robust solution for errors in time-interval data conversion.
- This method enhances the accuracy of demographic data, particularly for age-related event schedules.