Leading this session were Robert Goerge and Bong Joo Lee of Chapin Hall. It covered:
- Point-in-time versus longitudinal analysis
- Ecological fallacy
- Small cell size
- Adjusting rates with individuals and communities with regression
- Percentages versus rates in populations
Point-in-Time Versus Longitudinal Analyses
One way to look at foster care is through point-in-time analyses. Another way is to look at the history of an entire entry cohort. Each approach gives different information. The latter approach will reveal time spent in care and show the distribution of care over time. The longitudinal approach is useful in examining what effects the length of time spent in care and point-in-time analysis can overrepresent the number of children who spend a long time in care.
Using aggregated data to make inferences at smaller geographic levels can be complex. Bong uses the example of infant mortality rates across geographic areas. By examining the relationship among key risk factors and infant mortality rates, Bong can account for about 1/3 of the seeming geographic variability in those rates. By considering such factors as the utilization of prenatal care, more of this variability can be explained.
Small Cell Size
The small size of populations in some geographic areas means that random events can produce substantial variation in incidence, service use, or other statistical measures applied to those areas. One way to compensate for small cell sizes is to simply analyze larger populations. Another possibility is to combine cohorts across years to create a multiyear moving average that compensates for the possibility of extreme variation.
Adjusting Rates with Regression
Lee also discussed the use of regression analysis to help untangle the influences on different variables in a community. In the discussion that followed, Lee and the participants covered how regression analyses can be used in planning and explaining what data show to communities.