| Usual Opposition Position |
| Statistical averages of cohort groups are frequently used to assess earning capacity and worklife expectancy. Some believe that use of statistical averages for specific plaintiffs is inappropriate |
| VEI Position |
| Averages from various populations have long been accepted as a means for prediction – life expectancy,
earnings, and others. No statistic, no matter how fine-tuned, can provide an exact predictor of an
individual’s future. This is as true of worklife expectancies as it is of various
measures of annual earnings and growth and discount rates.
The expert must use available statistics about populations and mold
them to meet the specifics of the case. As
noted by Marcia Angell in Science on Trial (1997, p. 115): Courtroom trials are not about populations, they are about individuals. . . . We have no basis, at least in the current state of knowledge, for making a judgment about a particular woman. We therefore must appeal to epidemiological data – that is, studies of populations. The United States Supreme Court recognized this uncertainty several years ago, in their decision in Jones and Laughlin Steel Corporation v. Howard E. Pfeifer 462 U.S. 523 (1983):By its very nature the calculation of an award for lost earnings must be a rough approximation. Because the lost stream can never be predicted with complete confidence, any lump sum represents only a “rough and ready†effort to put the plaintiff in the position he would have been in had he not been injured. Economists, actuaries, insurance companies, and gambling establishments use population averages when making rational bets on human outcomes. The basic belief is that in the absence of more specific and precise information, the best predictors of outcomes are statistical averages or relative frequencies. Following this, it is not true that disability data would have to be disaggregated by type, severity, or duration of disability in order to be reliable or meaningful.Even if segregated data existed, its use would be limited at best. Persons with the same diagnosis and the same length of time since injury can have dramatically different experiences in terms of their experience in the workplace, especially when education level is factored in. Consider an example of two men with identical hand injuries resulting in reduced grip strength and limited range of motion. This injury would have an enormous impact on a carpenter, who would likely need to leave his employment. For an English professor, however, the effect may be minimal. What the criticism does point to, however, is the fact that statistics of all sorts must be used responsibly and applied by persons familiar with issues involved. When assessing persons with disability, for instance, the user must be familiar with the effects of impairment on ability to work and earn money as well as the experiences of persons with disability in the labor market. |
| Related Articles | ||
| Gamboa & Holland (2005) | Gibson & Gluck (2000) | Gluck & Sachnin (2000) |
| Pflaum, et al. (2003) | Staller, Sullivan, & Friedman (2000) | |
Last modified: Tuesday October 14, 2008 03:35 PM