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The loglinear model as a tool for the analysis of demographic data
The Egyptian Population and Family Planning Review
|June 1, 1990
Summary
Loglinear models enhance demographic analysis by examining individual data in contingency tables. This technique clarifies fertility differentials, showing how variables impact birth intervals when others are controlled.
Area of Science:
- Demographic Analysis
- Statistical Modeling
Background:
- Traditional demographic analysis often relies on aggregate data, limiting nuanced understanding of individual-level factors.
- Analyzing fertility differentials requires methods capable of handling complex interactions between multiple variables.
Purpose of the Study:
- To demonstrate the application of loglinear models in demographic research.
- To analyze the determinants of fifth-birth intervals using individual-level data from the 1980 World Fertility Survey for Sudan.
Main Methods:
- Utilized loglinear models for the analysis of contingency tables.
- Employed individual-level data from the 1980 World Fertility Survey (WFS) for Sudan.
Main Results:
- Loglinear models effectively improve the understanding of fertility differentials by using individual data.
- The analysis revealed how specific variables influence fertility processes when other factors are held constant.
Conclusions:
- Loglinear models offer a powerful technique for detailed demographic analysis.
- The study highlights the value of individual-level data in uncovering mechanisms behind fertility differentials.
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