Complex genetic diseases are thought to result from genetic susceptibility factors acting in conjunction with environmental, lifestyle or non-genetic factors such as infectious, chemical, physical, nutritional and behavioural exposures. In the past, researchers have used the case-control study design to investigate disease associations with non-genetic factors. Recently, new genetic information in the form of Single Nucleotide Polymorphisms (SNPs) has been integrated into these population health studies in an attempt to better understand the joint effects of non-genetic and genetic risk factors. However, conventional statistical methods for this study design are not powerful enough to detect such joint effects, even for studies with very large sample sizes. Jihyung Shin is developing new biostatistical methods to more efficiently extract information from case-control data about statistical interactions between genetic and non-genetic risk factors for disease. By developing extensions of the methodology to allow for missing information on genetic risk factors in a statistically valid way, her work can accommodate the analysis of disease associations with SNP haplotypes, which are combinations of genetic variants at several nearby SNPs on the same chromosome. This type of analysis can offer improved power over analysis of single SNPs for detecting the effects of genetic factors and their interactions with non-genetic risk factors. The ability to identify interactions between genes and non-genetic factors that affect the risks of complex genetic disorders will improve our understanding of disease pathogenesis and help with the development of more effective and appropriate treatments, prevention and screening tools.