The Use of Multi-State Life Tables in Estimating Places for Biomedical and Behavioral Scientists A Technical Paper (1997) / Chapter Skim
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THE DATA
THE DATA
Pages 11-16
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From page 11... ...
These individuals were to be kept in the sampling Came for 42 years from the time they were first sampled.is The sample used to generate the estimates included only those respondents who reported valid information in two adjacent surveys on employment status, occupation, birth year, and U.S. employment location in both the initial and lathe sampling strategy changed significantly in 1991 when the sampling frame was Emoted to Pose who (~)
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From page 12... ...
As with retirement rates, the mobility rates were based on the observed proportion of personnel moving out of or into a field over a two-year period. In the case of biomedical out-migration, for example, the rate was defined as the proportion of persons moving from the biomedical workforce state to a nonbiomedical workforce state between two survey cycles.
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From page 13... ...
For Me workforce below the age of 70, Tiemeyer's male and female rates were combined to produce a rough approximation of We aggregate rates by weighting the male rates by two-thirds and the female rates by one-~ird. The estimated death rate for the workforce aged 70 and over was derived as an "educated guess." number needed to support a given projected rate of workforce growth.22 These new entrants were distributed by age based on SDR data from two pairs of adjacent surveys as shown in Appendix B.23 Summary of Flow Data The estimated transition rates generated from the SDR and the TIAA data are summarized by type of transition and period of analysis in Table 1.24 When averaged over all age groups within a period, these estimated rates look reasonable and do not display large amounts of variation.
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From page 14... ...
Mobility rates to other fields are in the 3 percent range in the biomedical workforce, and they are in the 2 percent range in the behavioral workforce. Mobility rates from other fields range from 0.6 to 0.9 percent in the nonbiomedical workforce and from 0.2 to 0.3 percent in the nonbehavioral workforce.25 There was 25It is not surprising to note that the means and standard errors of the mobility rates from nonbiomedical and nonbehavioral fields are substantially smaller than those for the other fields since they were generated from samples that were substantially larger than those of the biomedical and behavioral workforces.
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From page 15... ...
A commonly used statistical indicator of precision is the "standard error" of the estimate. This indicator is inversely related to precision (i.e., estimates with a small standard error are more precise than those 26The large range in retirement rates makes intuitive sense since almost no one retires from the younger cohorts (a very low agespecific rate)
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From page 16... ...
TABLE 2 Estimated Rangea Of Transition Rates by Type, Field, and Time Period ESTIMATED RANGE {in percentage points) Type and Field 1 973-1 979 1 979-1 985 1985-1991 M ORTALITY 9.90 9.90 9.90 RETIREMENT 35.45 30.79 33 99 M OBI LITY TO OTHER FIELDS Biomedical 17.62 13.89 9.44 Behavioral 12.22 6.73 6.53 FROM OTHER FIELDS Biomedical 2.67 2.26 2.29 Behavioral 4.02 0.99 0.73 aRange is defined as the difference between the high and the low age-specific transition rate.
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