Lunt Mark
Arthritis Research UK Epidemiology Unit, University of Manchester, Manchester, UK.
Rheumatology (Oxford). 2015 Jul;54(7):1137-40. doi: 10.1093/rheumatology/ket146. Epub 2013 Apr 16.
In many studies we wish to assess how a range of variables are associated with a particular outcome and also determine the strength of such relationships so that we can begin to understand how these factors relate to each other at a population level. Ultimately, we may also be interested in predicting the outcome from a series of predictive factors available at, say, a routine clinic visit. In a recent article in Rheumatology, Desai et al. did precisely that when they studied the prediction of hip and spine BMD from hand BMD and various demographic, lifestyle, disease and therapy variables in patients with RA. This article aims to introduce the statistical methodology that can be used in such a situation and explain the meaning of some of the terms employed. It will also outline some common pitfalls encountered when performing such analyses.
在许多研究中,我们希望评估一系列变量如何与特定结果相关联,同时确定这种关系的强度,以便我们能够开始理解这些因素在人群层面上是如何相互关联的。最终,我们可能还会对根据例如在常规门诊就诊时可获得的一系列预测因素来预测结果感兴趣。在《风湿病学》最近的一篇文章中,德赛等人在研究类风湿关节炎患者手部骨密度以及各种人口统计学、生活方式、疾病和治疗变量对髋部和脊柱骨密度的预测时,正是这样做的。本文旨在介绍可用于这种情况的统计方法,并解释所使用的一些术语的含义。它还将概述进行此类分析时遇到的一些常见陷阱。