Schouten E G, Dekker J M, Kok F J, Le Cessie S, Van Houwelingen H C, Pool J, Vanderbroucke J P
Department of Epidemiology and Public Health, Agricultural University, Wageningen, The Netherlands.
Stat Med. 1993 Sep 30;12(18):1733-45. doi: 10.1002/sim.4780121808.
Multivariate analysis in case-base designs depends on approximate methods. In the present study, new pseudo-likelihood methods are developed for this design. With these methods, the case-cohort risk ratio and rate ratio as well as their standard errors are easily estimated using logistic regression and Poisson regression, respectively. This is illustrated by the association between hypertension and cardiovascular mortality in a cohort, estimated by case-cohort analysis, using samples of several sizes. The estimates are compared with those obtaining in full-cohort and nested case-control designs. The results indicate that these methods, which require nothing but widely available computer software, are valid. The case-cohort design, therefore, is a good, sometimes even advantageous alternative to the nested case-control design, in studying a disease that is not very rare. Application of the risk ratio method to the full cohort, using a 'sample' of 100 per cent follows logically; whenever the true risk ratio is desired instead of the odds ratio, a multivariate model for its estimation is therefore available.
病例对照设计中的多变量分析依赖于近似方法。在本研究中，针对该设计开发了新的伪似然方法。使用这些方法，病例队列风险比和率比及其标准误可分别通过逻辑回归和泊松回归轻松估计。通过病例队列分析，利用不同规模的样本，对一个队列中高血压与心血管死亡率之间的关联进行了说明。将这些估计值与全队列和巢式病例对照设计中获得的估计值进行了比较。结果表明，这些方法仅需广泛使用的计算机软件，是有效的。因此，在研究一种不太罕见的疾病时，病例队列设计是巢式病例对照设计的一种良好的、有时甚至更具优势的替代方案。将风险比方法应用于全队列，使用100%的“样本”在逻辑上是合理的；每当需要真实风险比而非比值比时，因此可使用多变量模型进行估计。
