Statistical Methods for Improving Causal Analyses

点击翻译按钮获取中文摘要

We are trying to develop statistical methods to help medical researchers in their search for causes of disease. A lot of medical research involves gathering data from people and using statistical models to tell us which factors cause later health. For example, we might ask a group of people about their diet as children, as teenagers and as adults, and use this to try to tell us whether poor diet causes cancer in later life.There are several problems with these studies that make it hard to draw conclusions. One is that people agreeing to be in a study are often different from people who don’t agree. Another is that people tend to drop out of a study over time – and again the people who drop out are often different from the people who stay. A third problem is that people change as they go through life – and we might want to know whether the cause of a disease happens at birth, or during childhood, or whether there are chances to prevent the disease even in adults. Statistical models may not give the right answers if any of these problems occur – and this could mean that the wrong health advice is given, or the wrong treatments developed. We aim to develop methods that can overcome these real-life problems, and help medical researchers to be more confident in their conclusions about causes of disease.