Roy-García Ivonne, Rivas-Ruiz Rodolfo, Pérez-Rodríguez Marcela, Palacios-Cruz Lino
Instituto Mexicano del Seguro Social, Centro Médico Nacional Siglo XXI, Centro de Adiestramiento en Investigación Clínica, Ciudad de México, México.
Rev Alerg Mex. 2019 Jul-Sep;66(3):354-360. doi: 10.29262/ram.v66i3.651.
The concept of correlation entails having a couple of observations (X and Y), that is to say, the value that Y acquires for a determined value of X; the correlation makes it possible to examine the trend of two variables to be grouped together. We know that, with increasing age, blood pressure figures also increase, therefore, if we want to answer a research question like "what is the connection between age and blood pressure?" the relevant statistical test is a correlation test. This test makes it possible to quantify the magnitude of the correlation between two variables, but it is also helpful for predicting values. If these variables had a perfect correlation, the value of the variable Y could be deduced by knowing the value of X. Because of these advantages, the correlation is one of the most frequently used tests in the clinical setting since, in addition to measuring the direction and magnitude of the association of two variables, it is one of the foundations for prediction models, such as linear regression model, logistic regression model and Cox proportional hazards model.
相关性的概念需要有一对观测值（X 和 Y），也就是说，Y 对于 X 的某个确定值所取得的值；相关性使得能够考察两个变量聚集在一起的趋势。我们知道，随着年龄增长，血压数值也会升高，因此，如果我们想要回答诸如“年龄与血压之间有什么联系？”这样的研究问题，相关的统计检验就是相关性检验。该检验能够量化两个变量之间相关性的大小，但它对于预测值也很有帮助。如果这些变量具有完全相关性，那么通过知道 X 的值就可以推断出变量 Y 的值。由于这些优点，相关性是临床环境中最常用的检验之一，因为除了测量两个变量关联的方向和大小之外，它还是预测模型（如线性回归模型、逻辑回归模型和Cox 比例风险模型）的基础之一。
