Epidemiology and Biostatistics Department
Melanie Bell, PhD, MS is a Professor in the Department of Epidemiology and Biostatistics at the Mel and Enid Zuckerman College of Public Health. Her research focus is methods for handling missing data in intervention and cluster randomized trials, patient reported outcomes, and on research methods evaluation. She is currently engaged in collaborative research in the fields of cancer, tobacco cessation, psycho-oncology, cardiovascular disease prevention, and health inequities. Her past collaborations include research in the fields of sexual health, physical activity and nutrition. Dr. Bell has most recently worked at the University of Sydney with a cancer trials group focusing on quality of life and other patient reported outcomes. She taught several workshops while in Australia, including Design and Analysis of Quality of Life Trials, Avoiding Common Statistical Errors, and Designing Intervention Studies. Before this, she was a senior lecturer at the University of Otago in Dunedin, New Zealand. Dr. Bell earned her PhD in Biostatistics from the University of Colorado Health Sciences Center in 2002, an MS in Mathematics in 1992 from Northern Arizona University, and an AB in Mathematics from Occidental College in Los Angeles, in 1990. Recent papers on missing data are:
Fiero MH, Hsu C, Bell ML (2017) Missing data sensitivity analysis: pattern mixture models for cluster randomized trials. Statistics in Medicine. Epub 7 Aug 2017
Fiero M, Huang S, Oren E, Bell ML. (2016) Statistical analysis and handling of missing data in cluster randomized trials: a systematic review. Trials. 2016 17:72..
Bell ML, Fiero M, Horton NJ, Hsu C. (2014) Handling missing data in RCTs; a review of the top medical journals. BMC Medical Research Methodology. 14:118.
Bell ML, Fairclough DL. (2014) Practical and statistical issues in missing data for longitudinal patient reported outcomes. Statistical Methods in Medical Research. 23(5):440-459.
Bell ML, Kenward MJ, Horton N, Fairclough DL. (2013) Differential dropout and bias in randomised controlled trials: when it matters and when it may not. BMJ. 2013; 346: e8668.