Jacquez G M
BioMedware, Inc., Ann Arbor, MI 48105.
Am J Epidemiol. 1994 Jul 1;140(1):58-64. doi: 10.1093/oxfordjournals.aje.a117159.
Cuzick and Edwards (JR Stat Soc [B] 1990;52:73-104) have proposed a case-control test to detect spatial clustering. The test statistic is the sum, over all cases, of the number of each case's k nearest neighbors that also are cases. Their approach is attractive in that it accounts for geographic variation in population density and because it allows one to account for confounders, both known and unknown, through the judicious selection of controls. However, the test assumes case locations are known exactly, when, in practice, case locations are usually approximated by the centers of areas such as census tracts and zip code zones. In such situations, "ties" arise when cases and controls are assigned to the same area, and the loss of information precludes calculation of the test statistic. The author's approach enumerates the ways in which the ties may be resolved to obtain upper and lower bounds on the exact, unobserved, test statistic. The null hypothesis of no clustering is rejected when the upper and lower bounds are significant, and it is accepted when they are not significant. Judgment is withheld when the upper bound is significant but the lower bound is not significant. This approach allows Cuzick and Edwards' test to be used with inexact locations typical of most cluster investigations.
库齐克和爱德华兹（《皇家统计学会学报》[B辑]，1990年；52卷：73 - 104页）提出了一种用于检测空间聚集性的病例对照检验方法。检验统计量是所有病例中，每个病例的k个最近邻中也是病例的数量之和。他们的方法很有吸引力，因为它考虑了人口密度的地理差异，并且通过明智地选择对照，能够考虑已知和未知的混杂因素。然而，该检验假设病例的位置是精确已知的，而在实际中，病例位置通常由诸如普查区和邮政编码区等区域的中心来近似。在这种情况下，当病例和对照被分配到同一区域时会出现“平局”情况，信息的丢失使得检验统计量无法计算。作者的方法列举了平局情况可能的解决方式，以获得精确但未观测到的检验统计量的上下界。当上下界都具有显著性时，拒绝无聚集的原假设；当上下界都不具有显著性时，接受原假设。当上界具有显著性而下界不具有显著性时，暂不做判断。这种方法使得库齐克和爱德华兹的检验能够用于大多数聚集性调查中典型的不精确位置情况。
