Metodi di campionamento negli studi epidemiologici

F. Franco, A. di Napoli
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引用次数: 2

Abstract

Sampling methods in epidemiological studies Sampling allows researchers to obtain information about a population through data obtained from a subset of the population, with a saving in terms of costs and workload compared to a study based on the entire population. Sampling allows the collecting of high quality information, provided that the sample size is large enough to detect a true association between exposure and outcome. There are two types of sampling methods: probability and non-probability sampling. In probability sampling the subset of the population is extracted randomly from all eligible individuals; this method, as all subjects have a chance of being chosen, allows researchers to generalize the findings of their study. In non-probability sampling, some individuals have no chance of being selected, because researchers do not extract the sample from all eligible subjects of a population; the sample is probably non-representative, the effect of sampling error cannot be estimated, so that the study produces non-generalizable results. Examples of probability sampling methods are: simple random sampling, systematic sampling, stratified sampling, and clustered sampling. Examples of non-probability sampling methods are: convenience sampling, judgement sampling.
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流行病学研究中的抽样方法
流行病学研究中的抽样方法抽样使研究人员能够通过从人口的一个子集获得的数据来获得有关人口的信息,与基于整个人口的研究相比,在成本和工作量方面节省了很多。抽样可以收集高质量的信息,只要样本量足够大,可以发现暴露与结果之间的真正联系。抽样方法有两种:概率抽样和非概率抽样。在概率抽样中,从所有符合条件的个体中随机抽取总体的子集;由于所有的研究对象都有机会被选择,这种方法使研究人员能够概括他们的研究结果。在非概率抽样中,有些个体没有机会被选中,因为研究人员不会从人群中所有符合条件的受试者中提取样本;样本可能不具有代表性,抽样误差的影响无法估计,因此研究产生的结果不可推广。概率抽样方法的例子有:简单随机抽样、系统抽样、分层抽样和聚类抽样。非概率抽样方法的例子有:方便抽样、判断抽样。
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