CALCULATING CONFIDENCE-INTERVALS FOR RELATIVE RISKS (ODDS RATIOS) AND STANDARDIZED RATIOS AND RATES
CALCULATING CONFIDENCE-INTERVALS FOR RELATIVE RISKS (ODDS RATIOS) AND STANDARDIZED RATIOS AND RATES
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DOI：
10.1136/bmj.296.6632.1313
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发表时间：
1988-05-07
影响因子：
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通讯作者：
GARDNER, MJ
中科院分区：
文献类型：
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作者：
MORRIS, JA;GARDNER, MJ
Gardner和Altman解释了在分析研究中使用估计和置信区间进行推断的基本原理，并描述了他们对平均值或比例及其差异的计算。在本文中，我们提出了计算从医学调查中获得的其他常见统计数据的置信区间的方法。描述了获得相对风险估计的置信区间的技术。这些数据可以来自发病率研究，例如，在两组确定的母亲中比较出生时先天畸形的频率，或者来自病例对照研究，其中一组患有感兴趣的疾病的患者（病例）与另一组没有疾病的人（对照）进行比较。本文描述了在发病率、患病率和死亡率研究中获得标准化疾病比率和发病率置信区间的方法。这些比率和比率通常是经过计算的，以便在调整年龄和性别等混杂因素后，在研究组之间进行适当的比较。最常用的标准化指标是标准化发病率比（SIR）和标准化死亡率比（SMR）。虽然中间步骤显示为四舍五入的结果，但计算已达到完全的算术精度，这是推荐的做法。本文给出的一些方法是大样本近似，对于少于20例的研究是不可靠的。对于这些类型的研究，必须遵守适当的设计原则，因为置信区间只传达抽样变异对估计统计量精度的影响，不能控制其他误差，如由于选择不适当的控制或收集数据的方法而产生的偏倚。
Gardner and Altman explained the rationale for using estimation and confidence intervals in making inferences from analytical studies and described their calculation formeans or proportions and their differences.'In this paper we present methods for calculating confidence intervals for other common statistics obtained from medical investigations. The techniques for obtaining confidence intervals for estimates of relative risk are described. These can come either from an incidence study, where, for example, the frequency of a congenital malformation at birth is compared in two defined groups of mothers, or from a case-control study, where a group of patients with the disease of interest (the cases) is compared with another group of people without the disease (the controls). The methods of obtaining confidence intervals for standardised disease ratios and rates in studies of incidence, prevalence, and mortality are described. Such rates and ratios are commonly calculated to enable appropriate comparisons to be made between study groups after adjustment for confounding factors like age and sex. The most frequently used standardised indices are the standardised incidence ratio (SIR) and the standardised mortality ratio (SMR).A worked example is included for each method. The calculations have been carried out to full arithmetical precision, as is recom-mended practice, 2 although intermediate steps are shown as rounded results. Some of the methods given in this paper are large sample approximations and are not reliable for studies with fewer than about 20cases. Appropriate design principles for these types of study have to be adhered to since confidence intervals convey only the effects of sampling variation on the precision of the estimated statistics andcannot control for othererrors such as biases due to the selection of inappropriate controls or in the methods of collecting the data.