population of interest. Selection bias occurs when the study participants differ from nonparticipants in characteristics that might not be observed, that is, when the groups differ in measured or unmeasured baseline characteristics because of how participants were selected or assigned. Information on age would have to be captured, given the distribution of age among military personnel and the possibility that age is a confounding factor.
As discussed above, adequate sample size is critical in conducting a well-designed epidemiologic study. A previous Institute of Medicine (IOM) report discussed the importance of adequate sample size for studying the health of Gulf War veterans: “sufficient samples sizes for each cohort in the study are crucial to ensure adequate statistical power to find differences as well as to reliably identify the lack of differences between groups” (IOM, 1999).
Sample-size calculations are based on the expected magnitude of the difference between the exposed and unexposed groups, the relative sizes of the groups to be compared, and specified levels for type I error (the error of rejecting the null hypothesis when it is true) and type II error (the error of failing to reject the null hypothesis when the alternative hypothesis is true). Adequate followup time is also important, especially if the health outcome of interest has a long latent period (latency, followup, and other factors that should be taken into consideration in calculating sample size are discussed in more detail later in this chapter).
To gain a sense of the expected sample sizes required for a high-quality epidemiologic study, the committee generated sample-size estimates for a cancer outcome (lung cancer) and a renal-function outcome (serum creatinine concentration). Those outcomes were selected because they are among the ones identified as having high priority for further study by the committee in its report Gulf War and Health: Updated Literature Review of Depleted Uranium (IOM, 2008). Sample sizes for other high-priority health outcomes (lymphomas, respiratory disease, neurologic outcomes (including neurocognitive outcomes), and adverse reproductive and developmental outcomes) and for mortality should also be considered. Those outcomes may be defined either by the diagnosis of a specific disease entity (such as lymphoma) or by measurement of an important physiologic variable (such as serum creatinine or forced expiratory volume in 1 second as an indicator of renal function or lung function, respectively).
The committee estimated the minimum sample size required for detecting a statistically significant difference in risk of lung cancer between DU-exposed and unexposed subjects. Given that lung cancer is one of the more common can-