Brass Relational Logit Alpha Beta
Fit a life table with the Brass relational logit system Y_fit = alpha + beta * Y_standard applied through logit(s) = 0.5 ln((1-s)/s), returning fitted survivorship values for each standard survival probability.
Description
Fit a life table with the Brass relational logit system Y_fit = alpha + beta * Y_standard applied through logit(s) = 0.5 ln((1-s)/s), returning fitted survivorship values for each standard survival probability.
Fit a life table with the Brass relational logit system Y_fit = alpha + beta * Y_standard applied through logit(s) = 0.5 ln((1-s)/s), returning fitted survivorship values for each standard survival probability.1
When to use Brass Relational Logit Alpha Beta
Use this mortality or life-table method when age intervals, deaths, exposures, survivorship, and open-ended interval assumptions refer to the same population and period.
- Alpha
- Level parameter alpha of the relational system.
- Beta
- Slope parameter beta of the relational system.
- Standard l(x)
- Standard life table survival probabilities l(x), each strictly between zero and one.
How the method works
- Fitted l(x)
- Fitted survival probabilities l*(x) for each standard value.
Limitations and assumptions
Life-table results depend on age grouping, exposure quality, the treatment of the first and terminal intervals, and assumptions about deaths within each interval. Sparse deaths can make rates unstable.
Alternative or Complementary measures
Complement a summary mortality result with age-specific death rates, survivorship, and exposure counts. A complete life table is preferable when the question involves several ages or remaining life expectancy.
References
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Life table — Wikipedia contributors
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