Journal of Biometrics & Biostatistics

Susan Wells

Publications

• Research Article
  Using Directed Acyclic Graphs for Investigating Causal Paths for Cardiovascular Disease
  Author(s): Simon Thornley, Roger J Marshall, Susan Wells and Rod JacksonSimon Thornley, Roger J Marshall, Susan Wells and Rod Jackson
  
  By testing for conditional dependence, algorithms can generate directed acyclic graphs (DAGs), which may help inform variable selection when building models for statistical risk prediction or for assessing causal influence. Here, we demonstrate how the method may help us understand the relationship between variables commonly used to predict cardiovascular disease (CVD) risk. The sample included people who were aged 30 to 80 years old, free of CVD, who had a CVD risk assessment in primary care and had at least 2 years of follow-up. The endpoints were combined CVD events, and the other variables were age, sex, diabetes, smoking, ethnic group, preventive drug use (statins or antihypertensive), blood pressure, family history and cholesterol ratio. We used the ‘grow shrink’ algorithm, in the bnlearn library of R software to generate a DAG. A total of 6256 individ.. Read More»
  DOI: 10.4172/2155-6180.1000182

  Abstract PDF